**2. Knowledge processes in joint industry-academia research projects**

Subsection 2.1. presents the context of joint industry-academia research projects and why it is of interest to deepen the study of knowledge processes in this context. Subsection 2.2. examines the KM literature about knowledge processes and focuses on two of them: knowledge creation/generation and knowledge sharing/transfer. It clarifies in highlight boxes the conceptual and theoretical basis of the chapter and its expected outputs. Considering the context of joint industry-academia research projects, subsection 2.3. concludes with additional points.

### **2.1 Joint industry-academia research projects and KM activities**

For political, economic, and pragmatic reasons, joint industry-academia research is developing. As mentioned in [5], "most funded calls for research put pressure on researchers to conduct collaborative research with companies and to produce more value for industry and society. Companies are looking for external expertise (an alternative from consultancy); they seek to diversify the partners who participate in their open innovation processes and expect to gain useful knowledge from researchers. Academics, on the other hand, are looking for 'problems' with practical relevance that fit with their research interests, or theoretical challenges linked to practice issues, combined with funding… that could lead to 'something new' for theory, with good potential for publication or dissemination".

Even when knowledge creation is not a goal per se in industry-academia research projects, these projects are propitious to knowledge exchanges/sharing between partners as well as to knowledge generation/creation. This explains why knowledge creation and protection are often explicitly stated points in university-industry research agreements and contracts [7].

Different types of knowledge processes are generally taken into consideration and call for specific treatments in research industry-academia agreements with regards to intellectual property. Whether knowledge creation is one of the expected outputs of a project, or, considering that interactions during the project might generate knowledge, further use of this "common knowledge" always explicitly makes part of research contracts. Even if it is generally the first to be mentioned and experienced during any collaborative research project, the question and status of knowledge sharing is less clear. To cover these exchanges, most agreements include a confidentiality section and try *ex ante* to identify the "prior knowledge" of partners to protect it.

Most partners engaged in such projects are interested by learning from others and to benefit from their knowledge. However, there is sometimes an asymmetry in the willingness to share knowledge. Industry sometimes imagines that it is possible to solve problem and/or innovate thanks to academic knowledge transfer and use, or that academics can work independently and bring solutions or innovation without interacting much with practitioners. Academics sometimes look for practice experiences to feed their research process without caring much about counterparts for practice. Collaborative research projects are challenging for both parties and the management of knowledge in these projects appears to be a key issue, although the literature does not talk much about this question.

Since our PhD dissertation and the beginning of our academic carrier, we have been doing research in collaboration with private companies and/or public organizations. Our ambition was twofold. On the one hand, we wanted to help them to solve logistics and SCM problems or to foresee their future and strategize, as well as to develop their logistics and SCM knowledge, competences, and capabilities. On the other hand, these collaborative projects were aiming at developing our knowledge base and creating significant knowledge in logistics and SCM. An in-depth analysis of our experience in joint industry-academia research projects [5] revealed the importance of industryacademia interactions to create knowledge, highlighted the role of industry-academia dialogue and co-construction, and proposed guidelines for improving dialogue and co-construction during such projects as well as quality of outputs for both parties.

This work suggested to launched new joint industry-academia research projects to deepen the knowledge processes at work, especially those ending with knowledge creation. Based on this new round of experience engaged in early 2018, the objective of this chapter is to try to better understand knowledge processes in joint industryacademia research projects aiming at producing knowledge with both managerial and academic relevance and value, i.e., being useful for companies and society, as well as being valuable from an academic point of view.

### **2.2 KM processes: review of the literature and research objectives in the context of joint industry-academia research projects**

Knowledge Management (KM), as an area of management studies, emerged in the 1990s. Since the beginning, the study of KM processes (also called KM

*The Dynamic of Knowledge Creation in Joint Industry-Academia Research Projects… DOI: http://dx.doi.org/10.5772/intechopen.101985*

activities [8]) is a core topic in KM research. There is no consensus about the number and nature of KM processes. For [9], the "four major processes consist of the process of creating the knowledge (including knowledge maintenance and updating), the process of storing and retrieving the knowledge, the process of transferring (sharing) the knowledge, and the process of applying the knowledge". Behind the semantic heterogeneity of the terms to describe KM processes/ activities, an analysis of 160 KM frameworks around the globe identifies "six broad categories of knowledge management activities which could be regarded in KM research and KM practice as general accepted basic KM activities" [10]. These categories are (ranked by frequency of presence in the studied frameworks): Share – that includes Transfer –, Create – that includes Generate –, Use – that includes Apply –, Store, Identify and Acquire knowledge.

Since we study joint industry-academia research projects explicitly aiming at creating new knowledge, "*Create/Generate*" is an expected core KM process in these projects. Since our intent is to favor interactions in joint industry-academia research projects, "*Share/Transfer*" is therefore an inevitable and somehow explicitly desired KM process in such projects, notably when partners want to learn from each other. Bearing in mind the overall list of KM processes, the research focuses on these two processes.

### *2.2.1 Knowledge creation/generation*

Knowledge creation and knowledge generation are often interchangeably used in the KM literature. They are generally included in the same category namely knowledge creation (see [10]).

Most KM papers mention knowledge creation as one of the core activities/ processes of KM. According to [11], "knowledge creation is often considered as the initial stage of the knowledge flow process", also called "spiral of knowledge creation" [12]. Even if authors (e.g. [12]) insist on the dynamic and dialectical nature of the knowledge-creating process and on the importance of its context, knowledge creation implicitly refers in the KM literature to a deliberate production process of new knowledge. Knowledge creation, "driven by curiosity or in response to a problem, refers to the deliberate and purposeful collation of observations, data, or facts to generate new or novel ways of understanding a particular phenomenon" [13]. Here, knowledge generation appears to be a sub-process of knowledge creation, the process that ends with new knowledge.

Knowledge generation is an KM process more recently studied compared to knowledge creation [14]. In the literature focused on knowledge generation, it is viewed as a complex and rather emergent phenomenon. More precisely in [14], knowledge is viewed as constructed in practice and in context, held within individuals and collectives through nets of interaction, at once forms and is formed by activity. Knowledge generation is a knowledge process as such reflecting the emergent and construct character of organizational knowledge [15], and "the value of knowledge for organizations and their members is increasingly linked with its construction within rapidly changing, often ambiguous and very specific contexts as well as in social settings" [14].

This overview of the create/share process in the KM literature suggests that knowledge creation can be viewed as a *result* or a *process*. The *knowledge creation process* can be viewed as a deliberate and purposeful production process and/or a dynamic, complex, never-ending dialectic spiral. *Knowledge generation* appears like an emergent, uncertain, and complex process producing "sticky" knowledge [16]. Behind the difference between knowledge creation and generation lies the ontological question of the nature of knowledge. KM literature balances between an

instrumental and positivistic view of knowledge, and a systemic and constructionist view [15], assuming its distributed, localized, paradoxical, and dialectical nature.

According to our experience of joint industry-academia research projects, it is worth considering separately knowledge creation and knowledge generation. In this chapter, *knowledge creation* refers to the *result* that can be a mix of expected – thus "deliberate" – and emergent "unexpected" knowledge. *Knowledge generation* refers to the *process* that results in knowledge creation. This process can combine deliberate and/or emergent aspects. We will keep in mind the two ontological perspectives about the nature of the knowledge as well as the importance of the context of/for this KM process.

### *2.2.2 Knowledge sharing/transfer*

Knowledge sharing is one of the most researched topics in the field of KM [11]. It is one of the most studied KM activity/process, one question being why and how people/organizations share or do not share knowledge. However, the KM literature addresses very different ways of "sharing" knowledge clearly mentioned by the words – transfer, distribution, communication, diffusion, dissemination – used in the "share" category in [10].

Many KM papers (e.g. [13]) adopt a classic sender-receiver communication approach of knowledge exchanges that can be mono directional or bi-directional. In this view, explicit knowledge (viewed like and object) can be *transferred* to an identified individual receiver or disseminated broadly to multi-individuals. Dynamic interactions (such as conversation, dialogue, sharing) call for another approach.

Knowledge transfer is an important research topic in KM. It has been studied within firms and in inter-organizational contexts such as mergers, alliances, partnerships, or open innovation/research projects. A transfer begins when both a need and the knowledge to meet that need coexist. The use of the "transfer" metaphor reflects a structural view of knowledge and the possible movement of knowledge [16], in general from an "expert" individual or organization to a "novice" one. The underlying assumption is that knowledge can be transferred through a communication channel and reused by the receiver.

According to contemporary epistemological approaches in knowledge management, "the notion of transfer is an insufficient and perhaps inappropriate objective for the development of knowledge" [14], in particular because of the stickiness of knowledge which nature is socially constructed, practice-based, context dependent, and tacitly held.

Knowledge sharing refers to situations where partners both have knowledge and find interesting to engage mutual exchanges of knowledge. Sharing is viewed as a gradual process generally including discussion and dialogue. Knowledge sharing implicitly "recognizes the complexity and elusiveness of knowledge, its situatedness, plurality, and entwinement with human understanding and interaction" [14].

Knowledge sharing is a dynamic context-dependent process [12, 15]. Therefore, the context of the process (time, space, conditions, participants, objectives, agenda, etc.) is of importance. In line with [12] and the notion of "*Ba*" (a common place or

According to our experience of joint industry-academia research projects, it is worth considering separately knowledge transfer and knowledge sharing. In this chapter, *knowledge transfer* refers to the *transmission* of knowledge while *knowledge sharing* refers to a more *dynamic*, *interactive,* and *situated mutual exchange* of knowledge. We bear in mind the importance of the context and of the "*Ba"* for knowledge sharing. Again, the ontological view of knowledge seems a key point in delineating between knowledge transfer and sharing.

*The Dynamic of Knowledge Creation in Joint Industry-Academia Research Projects… DOI: http://dx.doi.org/10.5772/intechopen.101985*

space for creating knowledge), it is possible to improve the conditions of the interactions and stimulate knowledge sharing.

### *2.2.3 Relationships between knowledge processes*

Heisig [10] mentions that KM activities/processes mutually complement each other and therefore require co-ordination. The unified model of dynamic knowledge creation in [12] also suggests the complementary nature of knowledge transfer, knowledge sharing and knowledge generation. Nonetheless, the KM literature does not develop much the relationships between knowledge processes that are often studied separately and viewed as sequential.

Our research intents to study what knowledge processes are at work in joint industry-academia research projects and to unveil the knowledge creation dynamic. Therefore, the objective is to study the relationships/interactions between knowledge transfer, sharing, generation ending with knowledge creation.

## **2.3 Additional considerations from the KM literature review of value in our context**

The context of our study and the review of the KM literature focused on knowledge processes suggest concluding Section 2 with two additional considerations.

### *2.3.1 The nature of knowledge: Bridging "schools"*

The KM literature, in particular some literature reviews or conceptual papers, mentions there are divergent streams of KM research linked to important questions about the knowledge definitions (and their implications), and the nature (ontology) of knowledge and KM.

Knowledge can be viewed [9] as a state of mind, an object, a process, a capability, with impact for example on how it can be observed, measured, etc. Debates about the definition and nature of knowledge has led to knowledge typologies, taxonomies, and lists of paradoxes (see "dichotomies" in [10]).

As mentioned in subsection 2.2., there are different ontological views of knowledge, leading to different epistemological approaches. A positivist approach views knowledge as an object, independent of the context, a resource that can be transferred, used. An interactionist, constructionist or constructivist approach considers that knowledge is sticky, cannot be dissociated from its context and that it is a dynamic phenomenon related to learning. The nature of knowledge led to debates (see [17]) and, according to [18], to fundamental errors in KM. There are different knowledge "perspectives" that although competing can be combined.

McIver et al. [19] bridges two theoretical schools of thought: the commodity or possession perspective (viewing knowledge as a resource or even an object) and the community or knowing perspective (a dynamic phenomenon that manifests itself in the very act of knowing something). The process of knowing highlights "the difference between *knowledge* which implies something that can be located and is independent and *knowing* which implies a process or action of knowers which is inseparable from them". Adopting a practice perspective, [19] proposes a multidimensional view of "knowledge-in-practice" combining two dimensions: *tacitness* and *learnability*.

Bridging the epistemology of possession and of practice, [20] draws from a pragmatist approach a distinction between *knowledge*, what is possessed, and *knowing*, what is part of action and is about relation. They do not see knowledge and knowing as competing, but as complementary and mutually enabling, and see the interplay of knowledge and knowing as a potentially generative phenomenon. "For human groups, the source of new knowledge and knowing lies in the use of knowledge as a tool of knowing within situated interaction with the social and physical world" [20]. Cook and Brown [20] emphasizes the importance of interactions and dialogue: "a conversation's back-and-forth not only dynamically affords the exchange of knowledge, it can also afford the generation of new knowledge, since each remark can yield new meaning as it is resituated in the evolving context of the conversation".

According to our research objectives, it is worth not choosing a knowledge view and questioning the relevance of articulating/bridging different knowledge views. The above proposals seem fruitful in the context of joint industry-academia research projects. They bolster the question of studying knowledge processes relationships/interactions.

### *2.3.2 KM enablers or barriers*

The KM literature includes studies looking at success factors for KM and KM enablers or barriers.

Some papers address success factors at a general KM level embracing all knowledge processes. Heisig [10] identified four categories of context factors which are critical for the success of KM activities: 1) Human-oriented factors: culture – people – leadership. 2) Organization: process and structure. 3) Technology: infrastructure and applications. 4) Management process: strategy, goals, and measurement. Based these categories, a systematic literature review of KM literature [8] lists every KM practice improving the performance of KM processes/activities that could be useful to analyze problems or suggest solutions.

Other papers address enablers or barriers to specific knowledge processes. As examples, [12] identifies factors facilitating the process of dynamic knowledge creation, and [16] proposes a taxonomy of barriers to intrafirm knowledge transfer.

Even if the study of enablers or barriers to knowledge processes and dynamics is not the core output of our study, we keep in mind these results that could be referred to or expanded in our context.
