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The Role of a Learning Approach in Building an Interorganizational Network Aiming for Collaborative Innovation (The Journal of Applied Behavioral Science, August 17, 2018)

Author: Yström, A., Ollila, S., Agogué, M., & Coghlan, D.

Yström, A., Ollila, S., Agogué, M., & Coghlan, D. (2019). The Role of a Learning Approach in Building an Interorganizational Network Aiming for Collaborative Innovation. The Journal of Applied Behavioral Science, 55(1), 27–49. https://doi.org/10.1177/0021886318793383

Abstract

Collaboration has become a common way for organizational actors to engage in problem solving and innovation. Yet shifting from strategic interactions (driven by reduction of transaction costs) to transformational interaction (driven by collaborative transorganizational development) appears to be difficult to achieve in practice in a network setting. This article argues that such a shift can be enhanced by adopting an action learning approach, which entails working on real-life problems without clear solutions and collectively working to resolve them. Based on an action learning research process, this article therefore explores ways to support collective knowledge creation within an interorganizational network setting. It provides rich illustrations of how the interactions in the network changed through the process, and the participants moved from a space of territorial protection to a space for collaborative exploration. From this case, the article outlines a model for learning in interorganizational networks and discusses related challenges.

Introduction

With increased demand for complex innovation and with a more distributed world, connecting across boundaries becomes a key organizing mechanism for innovation and hence organizational actors increasingly engage in co-creating solutions and experiences (Keys & Malnight, 2012) with actors from other organizations. This implies a shift from firm-centric innovation to network-centric innovation (Coughlan & Coghlan, 2011), acknowledging interorganizational collaboration as “networks of relationships” (Sharma & Kearins, 2011). For some organizations, network-centric innovation is a matter of survival and is necessary to stay in business. Accordingly, interorganizational relationships and the capability of firms to learn and draw from the knowledge shared by the different parties within the network become critical when facing rising and multifaceted demands (Chesbrough, 2003; Fryxell, Dooley, & Vryza, 2002; Inkpen & Li, 1999). It could be argued that working collaboratively across not only organizational but also sectoral and national boundaries to achieve “collaborative advantage” (Huxham, 1996) is now a common component in organizational life.
How to interact successfully under such complex circumstances to create innovation remains a practical challenge for many interorganizational arrangements such as alliances, networks, ecosystems, and platforms. Directing the attention to action and the practical doing of innovation includes the collective practice of organizational learning (Revans, 1971) and network or interorganizational learning (Coughlan & Coghlan, 2011). To exploit the advantages of inter-organizational learning members committed to both taking action and learning, a questioning and reflective process and a facilitator are needed (Coghlan & Coughlan, 2015). In other words, shared innovation processes and the learning they entail need to be managed and supported (Bergman, Jantunen, & Saksa, 2009; Buckley & Carter, 2002; Chesbrough & Teece, 2002) in order to enable a transition from a strategic to a transformational network (Coghlan & Coughlan, 2015). By strategic we infer that the focus of the interorganizational collaboration is on the economics of achieving greater efficiencies. By learning and transformational we mean conditions where a network learns as a system and adopts the transformation of its participating firms. Such a transition implies encouraging and facilitating an open flow of knowledge that fuel innovation and action learning in which all participants can benefit. However, to this date, few studies have been conducted to explore how to enable this shift, and this warrants further exploration from both a theoretical and practical point of view.
In this article, our particular focus is on the interactions in an interorganizational network setting where members of different organizations engage in collective knowledge creation as peers (Elmquist, Ollila, & Yström, 2016). We build on an action learning research process involving three of the authors working together with participants in a collective knowledge creation initiative, a kind of temporary and formal network in the automotive industry, with the purpose of facilitating a joint grant application process for public funding in collaborative innovation among six organizations exploring the boundary conditions of automated vehicles in a future transportation system.
The focus of the action learning research was on how to enable the interaction between the participants to transition from an initial hesitant mind-set to a sharing, trusting and explorative one in order to achieve the ambitions set out in the network. In designing the research, we used a design-based management tool for innovation, that is, the knowledge–concept–proposal (KCP) method (Elmquist & Segrestin, 2009; Hatchuel, Le Masson, & Weil, 2009) to invite the participants to engage in collective learning. The question underpinning the article is: How can a learning approach support collective knowledge creation in an interorganizational setting aiming for collaborative innovation?
A considerable amount of data was generated, and this article gives rich accounts of the process in which the action learning researchers were involved. We draw on theories on network action learning (Coghlan & Coughlan, 2015; Coughlan & Coghlan, 2011) to outline a model for learning in interorganizational network settings which explicates the transition process of the interaction from a strategic logic to a transformational one. Thus, the article makes a theoretical and a practical contribution to our current understanding of network learning and how to support collective knowledge creation from an organizational and managerial point of view.

Collaboration Challenges in Interorganizational Network Settings

Opening up the organizational boundaries to collaborate with others has become unavoidable in the search for creative outcomes to innovation problems. There is a range of possibilities for designing relationships with other organizations, including alliances, networks, communities, and platforms (West, 2014). Dyer and Singh (1998) suggest that a firm’s critical resources span firm boundaries and are embedded in interfirm routines and processes.
The concept of network competence stresses collaborative aspects and social qualifications such as ease of communication and reliability (Ritter & Gemünden, 2003; Ritter, Wilkinson, & Johnston, 2002). However, networks are generally not under the control of an individual firm but are more of self-organizing systems in which order emerges from the local interactions taking place (Wilkinson & Young, 2002). Indeed, interorganizational collaboration in networks can be challenging as it does not involve the use of control through legitimate authority (Lawrence, Phillips, & Hardy, 1999; Ouchi, 1980).
Besides, the more individuals and organizations are interacting, the more complex the aims and expectations become (Håkansson & Snehota, 1995). Thus, system boundaries are mostly unclear and actor preferences are both heterogeneous and evolving, leading to troubles in creating collective action (Huxham & Vangen, 2004). The goals and the purpose for the collaboration are thus continually moving targets (Rindova & Kotha, 2001), making best practices and contextual knowledge that build common ground and support coordination more difficult to share (Orlikowski, 2002). The ability to reflect upon and even contest meanings or uses may therefore be lacking (Levina, 2005), and the production of new practices or solutions through joint sensemaking among different collaborators becomes problematic (Hardy, Lawrence, & Grant, 2005). Fayard and Metiu (2014) argue that challenges of this kind are dialogical in nature and require recurring exchanges and learning among collaborators to be overcome. Complicated and slow decision-making processes can make the collaborative work tedious, and a realization that all partners are not working toward the same goal can make them lose faith in what they are doing. A summary of identified challenges in interorganizational collaboration is presented in Table 1.
Table 1. Theoretical Background: A Selection of the Challenges Identified in Interorganizational Collaboration.
Challenges Description References (partial)
No legitimate authority Not under the control of one individual firm Lawrence, Phillips, and Hardy (1999); Ouchi (1980)
Unclear system boundaries The scope of the collaboration is changing Huxham and Vangen (2004); Rindova and Kotha (2001)
Self-organizing system Order emerges from the local interactions taking place Wilkinson and Young (2002)
Actor preferences heterogeneous Hard to build common ground and joint collective action Huxham and Vangen (2004); Håkansson and Snehota (1995); Orlikowski (2002)
Network competence lacking Social qualifications such as ease of communication and reliability Ritter and Gemünden (2003); Ritter, Wilkinson, and Johnston (2002)
Joint sensemaking lacking Ability to reflect upon and contest meaning Hardy, Lawrence, and Grant. (2005); Levina (2005)
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When organizations are part of a pattern of multiple alliances, these alliances can be considered as a network of interorganizational interaction (Gomes-Casseres, 1996; Powell, 1990). Organizations in a network may work together to create value through coordinated efforts, particularly, in the presence of network effects. Docherty, Huzzard, de Leede, and Totterdill (2003) characterize three types of networks: strategic, learning, and transformational. The purpose of a strategic network is the reduction of transaction costs and the strategic network may operate and suffice for the duration of a contract with limited trust and guarded interactions. The purpose of the learning network is learning through exchanges of experience and the transformational network has the purpose of collaborative transorganizational development beyond the immediacy of current orders and contracts. Accordingly, it can be argued that to mitigate challenges in interorganizational collaboration aiming for collective innovation with the uncertainty and ambiguity it implies, a transformational network is needed. In this article, we build on the extant theories on challenges in interorganizational collaboration presented and introduce a learning perspective guiding our inquiry on how these challenges can be mitigated and how collective knowledge creation in an interorganizational network setting aiming for collaborative innovation can be supported.

A Learning Perspective

Action learning is considered an approach that enables an interorganizational collaboration to move from a strategic to a transformational mode of relating, and at the same time allows for researching that same process. While it is a term with many meanings, Coghlan and Coughlan (2015) argue that in essence, action learning is about participants working on real-life problems that do not appear to have clear solutions, and that participants meet on equal terms to report to one another and to discuss their problems and make progress in addressing them. Coughlan and Coghlan (2011) make the case that adopting an action learning approach enables networks to learn.
Network action learning is characterized by peer engagement in exploring and learning from addressing real issues in the network. Coughlan and Coghlan (2011) show how the continuous improvement process of direct, develop, and deploy in the firm (Slack & Lewis, 2008) becomes a collaborative improvement process of co-direct, co-develop, and co-deploy in the network. They demonstrate that action learning enables networks to develop from being strategic to becoming learning and transformational. They conclude that the adoption of an action learning approach, which entails the commitments to action and to learning, enacted through a questioning and reflective process based on operational data, enables the collaborative action and associated learning which underpins the transition to a transformational network (Coghlan & Coughlan, 2015).
In this article, we use the action learning framework of co-directing, co-developing, and co-deploying by Coghlan and Coughlan (2015). Based on this framework we consider learning to be a continuous circular process (see Figure 1) and we use the framework to analyze a case of interorganizational collaboration.
Figure 1. A framework guiding the inquiry of how to support collective knowledge creation in an interorganizational setting.
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Methodology

Research Design

This article is based on action learning research, a research design belonging to the family of action-oriented approaches to inquiry (Coghlan & Rigg, 2012; Coghlan & Coughlan, 2015; Coughlan & Coghlan, 2011). Action learning research operates in the space of practical knowing, where concern is for the practical. It shares the distinctive characteristic of all action-oriented approaches as it addresses the twin tasks of bringing about change in organizations and in generating robust, actionable knowledge, in an evolving process that is undertaken in a spirit of collaboration and co-inquiry, whereby research is constructed with people, rather than on or for them. The quality of the action learning research processes is grounded in the dual focus on both the inquiry process and the implementation process. Action learning research provides a basis for critical inquiry as it generates awareness and understanding of tensions, contradictions, power dynamics between organizations (Coughlan & Coghlan, 2011; Rigg & Trehan, 2004; Vince, 2004). It operates in the people-in-systems domain and applied behavioral and organizational science knowledge is both engaged in and drawn on.
The action learning research this article is based on focused empirically on a collective knowledge creation initiative, which can be characterized as a kind of temporary and formal network in the automotive industry. The research included action learning processes where three of the authors worked together with network participants and engaged in peer conversations that were based on the shared commitments to action and to learning and enacted through a questioning and reflective process about the emergent experiential and operational data. This provided a rich methodology and methods for the action research. We used a specific method called KCP to guide the learning process. A detailed description of the method is provided after a brief introduction of the empirical context.

The Empirical Context: The ABC Network

The ABC network, initiated in 2013, is set in the automotive industry in Northern Europe, where it has become increasingly more common to engage in networks and interorganizational projects of different forms (Ili, Albers, & Miller, 2010; Segrestin, 2005; Yström, 2013). The network had been formed as a result of a mutual interest in the development of automated vehicles, a crucial area for the partners involved and the future of the industry. Previous attempts by the organizations to individually receive funding had been unsuccessful, and the public funding agency had required that they submit a joint application. Therefore, the collective knowledge creation network involved six partners including large (competing) automotive companies such as AB Volvo, Autoliv, Scania, and Volvo Cars and was initiated by the vehicle and traffic safety center SAFER. SAFER is an association of companies such as AB Volvo, Autoliv, government agencies such as the Swedish Transport Administration, smaller technical consultancy companies, and universities such as Chalmers, the Royal Institute of Technology (KTH) and Gothenburg University, focusing on improving road safety.
Three individuals from a research institute were asked to form the management team of the network. It had been reported that the network experienced difficulties early on in defining a joint platform and a joint purpose. In an effort to tackle this challenge, the researchers were asked to participate as part of an action research process that could help the work to move forward. Three authors therefore started working in collaboration with these three managers in 2013. The managers were indeed eager to develop and test a method involving the participants that could increase the possibility of creating sustainable and utilizable results. Thus, this study was driven by an actual need and interest from practitioners to change something in their practice (Eden & Huxham, 1996).

Supporting the Learning Using a Tool for Collaborative Innovation: The KCP Method

To support the learning in the action learning research process, the researchers proposed applying the KCP method, which aims to organize innovative capabilities distributed among a large collective. Based on a theoretical framework from engineering design labeled “C-K theory” (Hatchuel, 2002; Hatchuel & Weil, 2009; Le Masson, Weil, & Hatchuel, 2010), the method was originally developed in collaboration with RATP, the public transport operator for the city of Paris. Since 2003, more than 60 KCPs have taken place in a range of companies in various contexts, within and outside France (Agogué & Kazakçi, 2014). A KCP method is typically carried out in three phases, each demarked by at least one workshop with invited participants (see Table 2).
Table 2. Outline of Phases in the KCP (Knowledge–Concept–Proposal) Method.
Phases K phase C phase P phase
Overall aim • Mobilization of existing knowledge • Formulating concepts and create workshops around disruptive ideas • Developing a design strategy
• Acquisition of new knowledge • Proposing roadmaps
Description Expanding the common knowledge among the collective (including knowledge from outside the field); the aim of the phase is to enable different actors to share not only existing knowledge from different expertise from inside and outside the firm (i.e., to share the state-of-the-art) but also pending questions and exploratory issues (i.e., to share the state-of-the-non-art) Team work around conceptual propositions aiming at providing a large number of creative ideas and building on the knowledge exchange from the first phase; this second phase is a set of creative workshops where usual creativity techniques are used to help participants to discuss strange propositions, crazy concepts. These initial concepts are chosen to be quite generative so that teamwork is useful to explore them in different ways, leading to the emergence of a variety of refined and elaborated ideas Building on discovered new knowledge and explored new ideas, the aim of the P-phase is to elaborate proposals, projects, perspectives to implement and nurture novel propositions within the firm. It is usually associated with discussions regarding internal organizational issues but also regularly leads to renegotiating the nature of the relationship of the firm with the rest of its ecosystem. This phase usually requires the longest preparation
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A team consisting of managers from the organization and external KCP-consultants or researchers usually organizes the setup of the KCP and guides the emergence of new knowledge and new ideas. Each phase necessitates iteration and reflection before moving into the next phase. The method is said to provide means to identify innovative value spaces that enable the development of innovative capabilities, the integration of both internal and external knowledge, the development of learning paths, and the identification of external collaborations (Elmquist & Segrestin, 2009). In the specific context of the ABC network, 15 to 20 participants from the six partner organizations and with primarily engineering backgrounds were involved in a series of workshops.

Data Collection and Analysis

The action learning research process that took place in the initial phase of the ABC network covering a period of approximately 18 months, comprised four steps and multiple sources of data, including numerous conversations and e-mailing with managers over a period of 18 months, 16 interviews with KCP experts and users, observations of three full-day workshops completed with field notes, an open-question survey post-workshop, as well as written documents produced by the managers over the whole period.
To analyze the data for the theoretical contribution, a grounded theory strategy advocated by Langley (1999) was followed. Data were continuously compared with the emerging theoretical insights (Glaser & Strauss, 1967). Since the research process was longitudinal it was possible to use a process approach to theorization (Langley, 1999) to depict the nature of the collaboration in relation to the phases in the KCP method and the various steps of the research process. Open coding (Strauss & Corbin, 2008) and memoing (Charmaz, 2014) was used to label raw data and these where discussed by the authors several times to record emergent hypotheses and synthesize the inductive findings. Table 3 presents an overview of the different steps in the action learning research process including data collection, main activities, and the questions intriguing the researchers and management.
Table 3. Overview of the Steps, Main Events, and the Intriguing Questions in the Action Learning Research Project.
Steps in action learning research project Sources of data collection Phase of KCP process Main activity Issues and challenges
Codirecting • Nine semistructured interviews with users and developers of KCP (2011) • Preparation phase (October 2011–March 2013) • Inquiring into the KCP process by interviewing and discussing with users and developers of the KCP process in France How is the KCP process operating and why? What are the underlying mechanisms? How could a method developed to enhance innovation within a firm be used to enhance innovation in a multi-actor context?
• Conversation with project management on open innovation challenges (2013) • Convening with French researcher on using the KCP process as an intervention in an open innovation context
• Semistructured interviews with CK-theory/KCP experts on adapting KCP to open innovation (2013)
• Field notes from initial workshop presentation at Traffic System Competence Group (2013)
• Document analysis of ABC project proposal/funding application (2013)
Codeveloping • Six meetings with ABC Management team (2013) • Invitation phase (March–May 2013) • Presenting the KCP process to the ABC project management The role of the researchers when doing intervention research? The role of the project management? How to bridge the competitive relationships of the participants? How to secure active participation and engagement of a wider group?
• 45 Hours of e-mailing and phone-calling (2013) • Dialoguing about and planning the setup of the three workshops including different roles
• Discussing whom to invite and how to formulate the invitation
Codeploying • Three full-day workshops with ABC project members (2013-2014) • Knowledge phase (August–September 2013) • Mobilization of existing knowledge by discussing with the ABC project management about other organizations or industries or sectors that have knowledge about automation, which could be of interest How to choose interesting and relevant presentations without giving any of the participants a pole position because the presentation is in line with their expertise? How to ensure that the presented knowledge is “pushing” the participants to expand their way of reasoning?
• Selection of presenters for the K-workshop and discussing with them about the KCP process and their role in it
• Planning the K-workshop
• K-workshop half-day September 2
• Reflections on the K-workshop and how to set up the C-workshop
• Concept phase (October–November 2013) • The research team is formulating conceptual propositions based on the K-workshop as well as the discussions with ABC project management How to frame crazy, provoking, and paradoxical concepts that still seem relevant for the participants? How to keep mind open and explorative and not go too quickly into solution mindedness? How to support and encourage confrontation, debate and knowledge sharing? From individual perspectives to joint sensemaking
• Selecting 8 concepts out of 10
• Creating mood boards, one for each concept
• Planning the C-workshop including group constellations and assigning concepts to the groups
• C-workshop half-day November 13
• The researchers act as facilitators when groups work on creating ideas from their concepts. Twenty-two ideas were developed at the C-workshop
• Reflections on the C-workshop and how to set up the P-workshop
• Proposal phase (December 2013–January 2014) • The research team is summarizing the ideas from the posters presented at the C-workshop How can commitment be created and retained? Trust and openness? How to include and convince other members in the participating organizations?
• A process for the P-workshop is created, which includes a vernissage with the ideas and voting what ideas to jointly explore
P-workshop whole day December 2
• The participants select four ideas to be explored jointly in the collaboration
• The collective sensemaking and commitment to define joint projects around the ideas constitutes a collaborative arena for the future work
Evaluating process and action • Evaluation survey from workshop participants (2013) • (August 2013–May 2014) • Reflections on and dialoguing around the KCP process and the future How can we go on together after the KCP process? The role of ABC project management?
• Field notes and documentation from workshops (2013)
• Conversation with ABC Management team (2014)
Note. KCP = knowledge–concept–proposal.
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Findings: A Learning Approach Supporting Collective Knowledge Creation

Already in the initiation of the action learning research project, a multitude of challenges associated with collaboration, which had been an obstacle for innovation and previous attempts to collaborate around automated vehicles, were articulated by the three individuals from the research institute constituting the ABC network management. It appeared that these individuals were highly concerned that the work in the network would suffer from, or even fail due to too little trust among the participants and too much politics, which would inhibit their learning from each other. In this section, we provide illustrative quotes from the conversations as well as notes from the observations to depict the challenges the members in the ABC network experienced, the collaborative action and learning activities, and the after-action reflection.

Collaborative Challenges and Risk for Collaborative Inertia

When setting up the ABC network, the management team faced the fact that even if the governmental agency providing the research funds required that certain organizations participated in the network, some of the partners did not even like to collaborate. One of the managers of the ABC network initially said that
they [the industrial partners] don’t like to collaborate, they don’t have the habit of collaborating, they don’t have that tradition, even when it comes to this area. I still think in their own minds they think that they can do this by themselves.
He continued to say that one of the biggest challenges the network faced was to find common ground and directions to move forward jointly:
In a sense, the difficulty is going from the politics and shaking hands in those big conventions to actual hands-on projects. And that is where I think this is going to hurt, when we say “Can you collaborate on this?” and they will say, “Oh, but that’s secret,” or “We are not interested in that area, we have another area that we are interested in,” and so on. So I think the challenge here is to extract the concrete examples of where we can collaborate, where we all agree.
Based on these first interviews, authors concluded that there was a concern that the participants would be unwilling to share information, unwilling to compromise, and locked into fixed positions/mind-sets, a diagnosis that the ABC network management team validated. The researchers then proposed KCP method as the process to be used to support collaborative action and learning for starting up the ABC network, and several face-to-face meetings and phone calls and e-mails were needed to dialogue around the KCP method. The ABC management claimed that the collaboration between some of the partners had historically suffered a severe blow, which made them worried that the participants would not be open-minded and share knowledge in the discussion, and therefore, they urged that the KCP process would facilitate openness and constructive dialoguing.

Action Learning: Inviting to Shared Commitment to Action and Learning

When adapting the KCP method to be a part of creating the ABC network by inviting the members to a collective space of reflection, learning, and implementation the researchers and the network management concluded that the initial steps were very important in order to get all the actors involved on board. This implied inviting participants to be peers rather than experts as well as identifying and framing a mode transcending organizational politics. When taking action, this meant that beyond the careful selection of the persons who were to be involved, any past conflicts as well as previous successful collaborations between the participants were thoroughly discussed. The invitation to the workshops was deliberately phrased to mitigate the power struggles, aiming to avoid old battles resurfacing based on conflicting positions. The intention was to set the scene for a collaborative focus emphasizing that no single actor could do this work on their own since there was too much uncertainty, but rather that they were dependent on each other and needed to learn from each other to safeguard the future of the industry in Sweden.

Action Learning: A Questioning and Reflective Process Supporting Learning

Following the KCP process, the K-workshop hosted five experts from adjacent fields (aviation and maritime) brought in to discuss automation from their point of view. Starting out by exploring areas where no one in the network could claim to be an expert was further strengthening the message that within the field of automation “we are all peers and we all gain from learning from each other.” The five presentations in the K-workshop triggered a lot of questions, discussions, and reflections among the participants. The researchers noted that the participants were very active in asking questions and sharing their reflections. Little of the feared political play, resistance, and silence could be observed. Also, the ABC network management team seemed very positive about the collaborative atmosphere that emerged during the K-workshop.
The next step according to the KCP process was the C-phase. Before the C-workshop, the researchers and the ABC network management team had prepared eight provocative concepts (e.g., “Driving an un-manned vehicle” about autonomous driving) that were worked on in four groups of four-to-six participants at the C-workshop. The workshop lasted half a day and the groups worked on each concept, made sense of it, discussed it, and came up with possible elaborations/extensions of the concept. The groups needed to create an elevator pitch describing their idea(s), including why the idea was relevant, what stakeholders needed to be involved in the further development of the idea, if there were any existing projects with links to this idea and what knowledge areas were needed to be explored to investigate the idea further.
During the C-workshop it could be observed that some of the participants had a hard time feeling comfortable in discussing hypothetical and speculative ideas not deriving from or being clearly based in the technical knowledge available. Some participants continuously brought up ideas in line with what they already were doing and even articulated irritation that the available knowledge was ignored. The researchers also facilitating the workshop had to remind the participants that they were not supposed to come up with clearly defined problems with solutions strongly attached to their own organizational or personal interests. In conversations during the breaks, the researchers and the ABC network managers discussed that they perceived a risk that if they could not keep the participants in the conceptual and ambiguous state, the conversations among the participants would move into a less trustful and more political mode.
Almost a month after the C-workshop, the P-workshop was carried out. The P-workshop was about reaching an agreement on what aspects related to the development of automated vehicles the ABC network should create around knowledge collectively. This implied an identification of areas for collaboration as well as confirmation of the joint commitment for this work. To secure the commitment of the participants and to build on what they had created during previous workshops, a voting procedure was organized when the 22 ideas resulting from the C-workshop needed to be reduced to 4. It could be observed that when discussing the 22 ideas in smaller groups before the voting, the participants were open about why they thought their organization would not want to collaborate on some ideas, for example, work in progress in some areas that some organizations did not want to reveal and, therefore, chose to stay outside a potential collaboration. In the end, it seemed easy for them to choose among the ideas and the participants seemed satisfied with the four areas chosen.

After-Action Reflection

After the three workshops and as the last part in the action learning research process, we conducted an after-action reflection focusing on the opinions of the participants about the process they had just been through, the experience of the ABC management team as well as the output of the process. The data from an evaluation survey showed that a large majority of the participants claimed that they found the workshop format helpful and that they felt satisfied with the outcomes. The ideas that came out of the peer conversations and collective action showed a significant variety, which the ABC management team in the final conversation claimed was unlikely to have happened if they had not applied such a structured method to explore new paths and support learning.
During the action learning research process, it became clear through our observations that embracing ambiguity and uncertainty implied a challenging paradigm shift for the ABC management team. Even though there were three senior researchers facilitating the process, the learning oriented way of working and the KCP method conflicted with the network managers’ traditional approach to management, in which they would focus on planning and controlling the interactions between the participants to accomplish knowledge exchange rather than inviting participants to learn and co-create. As stated by one of the managers:
The first session was like “WOW,” very different. [ . . . ] But in the end, I think the process was good. I actually think it worked well, and to be honest I didn’t think so in the beginning. I wasn’t sceptical, but rather worried that we wouldn’t make our deliverables.
Since the action learning research process was finalized, the ABC network has continued to work with three of the four ideas that was generated to form the foundation for future collaborative projects and funding applications related to the development of automated vehicles. Hence, it could be argued that the action learning process appears to have mitigated the challenge of power struggles and distrust and supported the sense of trust among the participants and an idea of how to jointly go on.

From a Strategic Network to a Transformational Network

Indeed, when reflecting on our findings, we specifically note that the nature and scope of the interaction between the participants in the network changed during the action learning research process. These observations together with the steps in the action learning process can be made sense of by using the framework of Coghlan and Coughlan (2015) to elaborate a model that explicates how such a transformation was supported (see Figure 2).
Figure 2. Development of interactions during the action learning process.
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The ABC network managers at least initially described the participants as reluctant to collaborate, as they were not used to collaborative settings and would rather conduct projects by themselves. Based on this we argue that the nature of the interactions in the network were more politically oriented, resembling that of transactional, closed, fearful, and careful. There was a risk when launching the ABC network that the participants would not trust each other, not share knowledge, or engage fully in the work since there had been unsuccessful previous attempts to get the same organizations and individuals to agree upon joint projects within the area of automated vehicles. The participating organizations could have been satisfied just keeping up the appearance of a collaboration, keeping an eye on each other, and advocating their own ideas and technology to be used without being interested in exploring jointly the ideas of others or completely new ones. Using action learning, including codirecting and codeveloping, supported dialoguing and inquiring into the area of joint interest which increased the level of trust and sense of commitment. Discussing the concrete areas where participants could agree to collaborate and jointly exploring new potential ideas regarding the future of the network, that is, co-deploying, further strengthened the trust, and thus, supported the transformation toward interacting in a more open, sharing, and collaborative way. In co-deploying, the participants deepened their understanding for the interest and priorities of the other partners in the ABC network and sealed the commitment for continuing collaboration. As this was the final phase of the KCP method, participants started to consider the implications of the process they had just been through for their organization. When an action learning process including questioning and reflecting comes to an end, there is always the risk of regressing to more transactional, closed, and fearful interactions, as the everyday organizational life with demands on deliverables and short-term results start to come to mind.

Discussion: Supporting Learning in an Interorganizational Network Setting Is to Support Collaboration

Shifting from strategic to transformational interaction appears to be difficult to achieve in practice in interorganizational network settings aiming for collaborative innovation. This article has set out to explore learning as a means of supporting collective knowledge creation by asking: How can a learning approach support collective knowledge creation in an interorganizational network setting aiming for collaborative innovation?

Framing Learning in Interorganizational Networks as a Circular Model

Our findings suggest that a learning approach, as developed and applied in the ABC network, mitigated some of the challenges associated with collective knowledge creation and collaboration. Drawing on theories on network action learning (Coghlan & Coughlan, 2015; Coughlan & Coghlan, 2011) and from the experiences of the ABC network, we outline a circular model for learning in interorganizational networks (see Figure 3). Our study shows that network was able to establish a collaborative platform for joint work. The developed model promotes learning as a collective of organizations as opposed to learning as an individual organization, and the former has been described in previous research as important, for for example, networks to be able to make the shift from being transactional to transformational (Coghlan & Coughlan, 2015).
Figure 3. A model for learning in interorganizational networks.
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The inner circle in the model illustrates the four phases of the applied method: inviting, knowledge mining, conceptualizing, and proposing. These phases form a collective knowledge creation cycle, and we relate them to the action learning cycle including co-directing, co-developing, and co-deploying, as proposed by Coughlan and Coghlan (2011), to highlight how action learning in interorganizational settings supports collective knowledge creation. The action learning process engaged the participants in peer conversations that were based on the shared commitments to action and to learning, and this supported the willingness to engage in collective knowledge mining and conceptualizing. These two processes contributed to the establishing of a transformational network, a kind of platform for future collaborative innovation.

Transitioning From Strategic to Transformational Network

The transition from strategic to transformational learning-oriented, open interaction was facilitated and supported by several features of the developed model, as illustrated in Figure 4.
Figure 4. From strategic to transformational interaction in networks.
OPEN IN VIEWER
First and foremost, participants were positioned as peers rather than experts by means of how the participants were invited, addressed, and related to throughout the process. This appears to be valuable especially as some of the participants had previous experience of failed collaboration with each other. Positions are crucial in collaboration since different positions come with different rights and duties (Harré & Langenhove, 1999), which guide people in how they can act. The peer position allows people to not know, to inquire, to co-create, and to have opinions that may not be fully developed. This is different from the position that most of the participants usually have in normal settings, as the expert position entails to provide solutions, give answers, and make claims without being questioned. In an interorganizational network, a peer position enables change in the nature of the interaction, from a transactional, closed, fearful, and careful, to a more open, sharing, and collaborative. As such, the model depicts how a learning approach invites participants to go beyond their own expertise furthering the notion that no single organization could achieve the results on their own.
The model also reflects the need to invite participants to explore new possibilities together rather than exploit old certainties (March, 1991). In interorganizational networks where there is a high level of politics and low level of trust it might be tempting or even easier for some participants to choose exploitation, that is, to consume the fruits of current capabilities, instead of going for the more risky and complex path of learning. Our conclusion is that managers of interorganizational networks can enable and support co-directing, co-developing, and co-deploying activities to guide participants to knowledge creation and exploration.
Furthermore, the model outlines a process that enables psychological contracting (Argyris, 1960; Rousseau, 1989) as it provides a platform for the participants as well as the management to dialogue around expectations and concerns (cf. Fayard & Metiu, 2014), thus, improving the level of trust and fostering “loyalty” and commitment to the network and its members (cf. Huxham & Beech, 2003; Newell & Swan, 2000). However, as concluded by, for example, Thorgren and Wincent (2011), too much trust between collaborative partners might also reinforce rigidities and create complacency.
Introducing action learning requires much from the management of the interorganizational network collaboration and can imply transforming from a planning and control mind-set to a reflecting and inquiring one. We know from previous research that to become successful, shared innovation processes need to be managed (Bergman et al., 2009), but our conclusion is that it needs to be managed in a way that supports collective learning. We also argue that the managers themselves might need help to be able to support the interaction in a way that enables cocreating solutions and experiences (Keys & Malnight, 2012; Schroll & Mild, 2011).
Many scholars have argued that knowledge creation is required for innovation (Lynn, Mazzuca, Morone, & Paulson, 1998; Madhavan & Grover, 1998; Wallin & von Krogh, 2010), implying that the mere facilitation of knowledge transfer (of existing knowledge) is not enough if innovation is the goal of the collaboration (see, e.g., Faems, Janssens, Madhok, & Van Looy, 2008). The proposed model forms a valuable contribution as it shows that action learning can alter the nature of the interactions as it pushes the interorganizational network out of a space of territorial protection and moves it in the direction of a space for explorative collaboration. Thus, action learning appears to be critical for enabling networks to develop from being strategic (where the focus is on the economics of achieving greater efficiencies) to becoming learning and transformational (where networks learn as a system and adopt the transformation of its participating firms (Docherty et al., 2003).

Conclusions and Managerial Implications

This article has shown the complexities and dynamic reality of implementing action learning to support collaboration in a collective knowledge creation initiative. We have described what emerged as a model for learning in interorganizational network settings aiming for collaborative innovation, at the actual interface of engagement. Our model depicts the shift from a strategic to a transformational network, as the action learning process changed the nature of the interactions and pushed the interorganizational network from a space of territorial protection into a space for collaborative exploration. Our findings confirm previous research on the value of a learning approach to develop collaborative capabilities at the interface of interorganizational network settings (Coghlan & Coughlan, 2015) and to support the transition from a strategic to a transformational network, as well as the need for a structured process to succeed with collective knowledge creation.

Contributions

Based on our empirical exploration of and reflection on this case on action learning we offer three contributions: to theory, to practice, and to methodology.

Contribution to Theory

The question underpinning this article focuses on the ways action learning can support collective knowledge creation in interorganizational network settings. The model proposed gives insights into how a network can shift from being strategic to being transformational by engaging in action learning, which helps change the nature of the interactions in the network. As such, we enriched existing knowledge of collaborative capabilities at the interface of networks (Coghlan & Coughlan, 2015), by theorizing around the concrete practices that support co-direction, co-development, and co-deployment.

Contribution to Practice

Action learning involves explicit processes of learning-in-action. There is no one best way for organizations to collaborate and move from being a strategic to a transformational network. It involves creating the space for conversation among peers that is grounded in a commitment to action and to learning and is enacted through a questioning and reflective process based on emergent experiential data. Our study shows that through the collaborative engagement with the real-life issues of the firms and the network, participants can come to learn about their own organizations and the network. Senior managers and those who represent their organizations at network meetings and initiatives can draw on the action learning philosophy and methods to create the collaborative environment and exploit the commitments to action and to learning. As evident in our study, for example, past experiences, preconceived notions and rivalry between parties are important to be aware of as they will undoubtedly influence the actions taken, but as our findings indicate, they can also be mitigated and resolved through the action learning process itself.

Contribution to Methodology

How operational and emergent data are gathered, generated, reflected, and acted on in this study provides a foundation for a robust research methodology and methods that are rigorous, reflective, and relevant. Our study shows the relevance and need of action learning research also in complex interorganizational network settings, where such a methodology can have significant impact on the development and learning in the network. What action learning actually entails in this particular setting is in our study made more concrete as we develop a framework guiding the inquiry of how to support collective knowledge creation in an interorganizational network setting and subsequently theorize around the practices that are involved in such learning.

Limitations and Future Research

We acknowledge the limitations of our current research. We offer insights and theorization building on a specific single case study in a specific industry and a specific policy-driven context. Such a single case study approach provides opportunities to develop an in-depth understanding of the practices of collaborative innovation but can limit the generalizability of our findings. Thus, further research is required to corroborate the findings. In particular, comparative studies are required to validate the model proposed in this article. Although the extent of research on interorganizational collaboration and innovation in networks is continuously increasing, the insights from this single case challenges such researchers to turn their contributions into actionable knowledge, not only to add to current theory but also to inform practice. Additional action-oriented studies, focusing on organizations as well as networks, in real time, hold great potential in adding to our understanding of the dynamics of implementation of collective knowledge creation processes.

Authors’ Note

An earlier version of this article was presented at the Academy of Management Conference in Atlanta, August 4 to 8, 2017 and awarded the ODC Best Action Research Paper Award.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Anna Yström https://orcid.org/0000-0003-4344-1685

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DMU Timestamp: July 13, 2023 21:18





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