**4. Results**

*Occupational Wellbeing*

**Table 1.**

*The study respondent's profiles.*

real-life experiences.

**3.6 Data analysis**

framework. This difference is explained by the concern of clarity which requires the use of terms understandable by the respondents and which are part of their reference scheme [52]. A first version of the guide has been served as a pre-test for our interview guide and aims to validate final interview guide. Two main versions of the interview guide were developed: a version (A) addressed to academics and industry and a version (B) addressed to government actors and consortia. These two versions take into account the particularities of the partner actors in collaborative projects and differ slightly and mainly in terms of the theme dealing with the progress of the project and knowledge management. Indeed, government actors and those belonging to the sub-sample of consortia do not actively participate in all project phases (especially in the execution phase) but are more involved in the initiation and set up phases some questions then differ from those asked of industrial and university partners. The interview guide consists of two parts. The first part involved general questions about the informants' background, their experience in collaborative projects. The second section focused on the main purpose of the study which is the determinants of knowledge sharing. The purpose of this section is to collect the information, experiences thoughts and interpretations of respondents regarding the progress of the collaborative's projects and its outcomes in terms of knowledge sharing. In addition, in this interview section, we often encouraged and asked respondents to provide us with concrete examples in order to enrich our data with

**Types of organizations Number of interviews**

Main contractors 15 SME 10 OEMs, Integrators and MROs- Tier One Suppliers 8 Governmental organizations and consortia 7 Universities and research centers 12 Total 52

The data analysis strategy adopted in our study follows the assumptions of the grounded theory. This strategy involves "the systematic comparison of small units of data (incidents) and the gradual construction of a system of" categories "that describe the phenomena being observed" [53]. The data has been condensed, structured and analysed. The data analysis followed the three types of coding of the grounded theory described by Corbin and Strauss [54], Corley and Gioia [55] and Charmaz [56]: open coding, axial coding and selective coding (or theoretical coding). To do so, we conducted line-by -line analysis of every quote to identify common ideas [57]. Through an iterative process, we defined a sub-category, and we established the link between the various categories by questioning causes, how, where and when [58]. Linking these categories allows us to assemble into higher order themes ([55]: 183). Thus, by establishing the relationships between categories and subcategories and integrating the concepts around the central themes, we can provide better explanations of the dynamic of knowledge sharing between collab-

orative project partners. The analysis is summarized in Appendix 1.

**164**

The purpose of this research was to better understand the factors driving the knowledge sharing in the context of inter-organizational collaboration. This work aims at analyzing how different determinants bolster the knowledge sharing process between partners. Based on the results of our primary data, these determinants depend on projects' phases as well as analysis level (macro, meso and micro). The research finding shows that the role of social proximity played an important role in the initiation project' phases, especially by fostering collaboration, but throughout the project its apport is controverted. As well, during this phase, the macro level, via the quasi- governmental institutions, helped fostering collaboration and knowledge sharing between aerospace partners. The team dynamic and the organization culture are more determinants in the set-up and execution project' phases while the role of macro level actors is less important.

### **4.1 Knowledge sharing and project' phases**

We deemed it appropriate to present the determinants and issues that influence collaboration between partners according to the phases in which they emerge. This choice is strongly influenced by the primary data which led us to classify the categories of determinants according to the project phases. These different phases are project initiation phase, project setup phase and the project execution phase. The determinants that influence knowledge sharing are related to three levels: micro, meso and macro. The purpose of this research was to better understand the underlying factors driving the knowledge sharing in the context of inter-organizational collaboration. The research finding shows that the role of social proximity in fostering collaboration is controverted. Despite the importance of the social proximity in collaboration, our results highlight that the outcomes of this collaboration, in term of success of collaboration and knowledge sharing, are questionable. In fact, our results reveal how the critical is the role that institutions play in facilitating collaboration among actors and creating an enabling environment for co-innovation. However, our results have also shown that despite the willingness and efforts of public actors to stimulate the process of co-innovation between actors, this objective does not seem to be easily achievable. The success of collaborative activity now depends on other determinants of individual and organizational nature, depending on the progress of the project.

## *4.1.1 The initiation project phase: the role of micro and macro level*

The initiation project' phases highlight the importance of the micro and macro level in the knowledge sharing process. It was particularly noticeable that informants argued that the macro level provides a great condition fostering knowledge sharing and collaboration. For example, the CRIAQ' forum, organized every two years, present the opportunity for the aerospace actors to openly display their issues and their research needs. The objective of those forum is to help organisations and academics to enhance their skills and develop their knowledge by sharing, exploring a new problematic. At this level, it is important to specify that the principal mission of CRIAQ is to bolster collaboration which is leads to knowledge sharing. However, some informants felt that, despite the role of CRIAQ fostering collaboration, the social capital is the most determinant element at this phase.
