**3. Research methodology**

## **3.1 Case study**

This research studies knowledge sharing between collaborative project partners within an innovative ecosystem. As the Quebecer aerospace ecosystem is an innovative ecosystem, it provides an interesting case for understanding collaborative projects and knowledge sharing processes. Our case of study is the projects of the Consortium for Research and Innovation in Aerospace in Quebec (CRIAQ ). The Consortium for Research and Innovation in Aerospace in Quebec (CRIAQ ) is a nonprofit organization (NPO) created in 2002 with the financial support of the Quebec government. Including companies of all size, academics and research centres as actors, CRIAQ aims to improve the collective knowledge base in the aerospace industry and to increase its competitiveness. CRIAQ operates in a network based on logic of open innovation and promotes collaboration between specialists from industry and researchers to identify and implement projects that meet industry requirements. His mission is to stimulate the ecosystem innovation by increasing collaborative projects and to enhance the skills and knowledge of aerospace actors. For CRIAQ projects, the funding structure determines the allocation of leadership within the team. Indeed, since the 50% of funding comes from NSERC (Natural Sciences and Engineering Research Council), it was agreed that leadership should be attributed to the university partner. As conceived by Etzkowitz and Leydesdroff [48], the CRIAQ model is strongly built on the interrelationship and interdependence between three spheres: state, industry and university and provides three analysis level: macro, meso and micro.

#### **3.2 Level of analysis**

Our objective is to understand the dynamics of knowledge sharing between the partners of the aeronautical sector. Thus, the unit of analysis focuses on individual involved in collaborative projects. However, we adopt a systemic analysis that includes the micro (individual), meso (organization) and macro (ecosystem) level.

#### **3.3 Data collection**

To collect data, we used semi-structured in-depth interview and documentation nevertheless, our main source of data collection is the semi-structured in-depth interview. The documentation as second source of data collection were collected through forum and steering committee records allows us to provide as much information as possible on the subject and field of our study, but also to triangulate our data sources. Regular follow-up interviews, secondary data analysis (internal documents), and corroboration activities were conducted to ensure that our findings match interviewees' view of reality. The triangulation of different data sources (interviews and documentation) makes it possible to identify converging lines, to corroborate information from other data sources [49]. As Eisenhardt [50] suggested, the data collection process was stopped when the interviews brought little or no more new information.

#### **3.4 Sampling**

As suggested by Eisenhardt [50] and Eisenhardt and Graebner [51], we conducted a theoretical sample by choosing cases that present a theoretical contribution for our study. As our sample is composed of 5 sub-samples: [18] main

**163**

meso and macro.

**3.5 Semi structured interviews**

*Managing Inter-Organizational Knowledge Sharing: Integrating Macro, Meso and Micro...*

contractors [19] integrators and Tier One suppliers [11] governmental and consortia organizations [7] universities and research centers and [39] SMEs, for the semi-structured interviews we sought theoretical saturation [50] in each category of respondents. This implies that we did not seek an equal number of interviews between the 5 subsamples. **Table 1** presents the respondent's profiles and the

In addition to academics, respondents hold the positions of: President, Vice President (Technology and Innovation), Vice President (R&D), General Manager, Project Director, Technical Director, R&D Director, Head of Department. These respondents are directly involved in CRIAQ projects at the decision-making and/or operational level. These different positions of informants involved in collaborative CRIAQ projects allows us to better understand the motivations of the partners, the context of the projects (decision making process to collaborate) which allows us a deeper analysis of the determinants that bolster the knowledge sharing between

However, two main criteria were important for the constitution of the sampling:

1.The sampling must include respondents belonging to each aeronautic ecosystem actors: major contractors, equipment manufacturers and SMEs, universities and research centers, public actors (ministries), and research consortia and another public-private organization involved in the aeronautical ecosystem and

2.The informant must be involved inclusively in (i) at least one completed CRIAQ project and (ii) another collaborative internal projects to their respective organizations. By the first element, which is at least one CRIAQ project, we sought to guarantee more richness of data through the experience of the respondent throughout all the CRIAQ projects phases. Thus, we excluded from our data analysis two cases of respondents who participated only in a CRIAQ project which is in progress, because we judged that the interviews were not sufficiently rich since the respondents did not necessarily have a complete vision of the project. Our objective is to understand the dynamic of knowledge sharing between partners in the aeronautical sector, it is therefore implicit that the respondents must have experienced all the phases of the collaborative project. However, without carrying out a formal comparative analysis between the two types of projects (internal and CRIAQ projects) in our analysis, for the second element, which is being involved in other collaborative projects internal to the organization, this will also allow us a deeper understanding of the dynamic of collaboration of the organization. This will essentially allow us to understand the impact of the two levels:

We conducted 52 semi-structured one -on- one interviews with various aerospace industry stakeholders involved in CRIAQ's projects including academics (professors), industrials and government institutions. The interview lasted approximately between 30 to 80 minutes and were conducted over an 11 months period. The interview process was based on an interview guide. Taking into account the flexible attitude adopted during interviews, this interview guide is more of an interview support and not a static interview guide and sets out the topics that should be covered during the interview. It is important to note that the terminology used in the interview guide is not the same as that used in the conceptual

*DOI: http://dx.doi.org/10.5772/intechopen.97830*

numbers of interviews conducted.

in connection with research consortia.

partners.

#### *Managing Inter-Organizational Knowledge Sharing: Integrating Macro, Meso and Micro... DOI: http://dx.doi.org/10.5772/intechopen.97830*

contractors [19] integrators and Tier One suppliers [11] governmental and consortia organizations [7] universities and research centers and [39] SMEs, for the semi-structured interviews we sought theoretical saturation [50] in each category of respondents. This implies that we did not seek an equal number of interviews between the 5 subsamples. **Table 1** presents the respondent's profiles and the numbers of interviews conducted.

In addition to academics, respondents hold the positions of: President, Vice President (Technology and Innovation), Vice President (R&D), General Manager, Project Director, Technical Director, R&D Director, Head of Department. These respondents are directly involved in CRIAQ projects at the decision-making and/or operational level. These different positions of informants involved in collaborative CRIAQ projects allows us to better understand the motivations of the partners, the context of the projects (decision making process to collaborate) which allows us a deeper analysis of the determinants that bolster the knowledge sharing between partners.

However, two main criteria were important for the constitution of the sampling:


## **3.5 Semi structured interviews**

We conducted 52 semi-structured one -on- one interviews with various aerospace industry stakeholders involved in CRIAQ's projects including academics (professors), industrials and government institutions. The interview lasted approximately between 30 to 80 minutes and were conducted over an 11 months period. The interview process was based on an interview guide. Taking into account the flexible attitude adopted during interviews, this interview guide is more of an interview support and not a static interview guide and sets out the topics that should be covered during the interview. It is important to note that the terminology used in the interview guide is not the same as that used in the conceptual

*Occupational Wellbeing*

**3.1 Case study**

**3. Research methodology**

analysis level: macro, meso and micro.

**3.2 Level of analysis**

**3.3 Data collection**

no more new information.

**3.4 Sampling**

This research studies knowledge sharing between collaborative project partners within an innovative ecosystem. As the Quebecer aerospace ecosystem is an innovative ecosystem, it provides an interesting case for understanding collaborative projects and knowledge sharing processes. Our case of study is the projects of the Consortium for Research and Innovation in Aerospace in Quebec (CRIAQ ). The Consortium for Research and Innovation in Aerospace in Quebec (CRIAQ ) is a nonprofit organization (NPO) created in 2002 with the financial support of the Quebec government. Including companies of all size, academics and research centres as actors, CRIAQ aims to improve the collective knowledge base in the aerospace industry and to increase its competitiveness. CRIAQ operates in a network based on logic of open innovation and promotes collaboration between specialists from industry and researchers to identify and implement projects that meet industry requirements. His mission is to stimulate the ecosystem innovation by increasing collaborative projects and to enhance the skills and knowledge of aerospace actors. For CRIAQ projects, the funding structure determines the allocation of leadership within the team. Indeed, since the 50% of funding comes from NSERC (Natural Sciences and Engineering Research Council), it was agreed that leadership should be attributed to the university partner. As conceived by Etzkowitz and Leydesdroff [48], the CRIAQ model is strongly built on the interrelationship and interdependence between three spheres: state, industry and university and provides three

Our objective is to understand the dynamics of knowledge sharing between the partners of the aeronautical sector. Thus, the unit of analysis focuses on individual involved in collaborative projects. However, we adopt a systemic analysis that includes the micro (individual), meso (organization) and macro (ecosystem) level.

To collect data, we used semi-structured in-depth interview and documentation nevertheless, our main source of data collection is the semi-structured in-depth interview. The documentation as second source of data collection were collected through forum and steering committee records allows us to provide as much information as possible on the subject and field of our study, but also to triangulate our data sources. Regular follow-up interviews, secondary data analysis (internal documents), and corroboration activities were conducted to ensure that our findings match interviewees' view of reality. The triangulation of different data sources (interviews and documentation) makes it possible to identify converging lines, to corroborate information from other data sources [49]. As Eisenhardt [50] suggested, the data collection process was stopped when the interviews brought little or

As suggested by Eisenhardt [50] and Eisenhardt and Graebner [51], we conducted a theoretical sample by choosing cases that present a theoretical contribution for our study. As our sample is composed of 5 sub-samples: [18] main

**162**


**Table 1.**

*The study respondent's profiles.*

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 real-life experiences.

### **3.6 Data analysis**

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

**165**

element at this phase.

*Managing Inter-Organizational Knowledge Sharing: Integrating Macro, Meso and Micro...*

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

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

*DOI: http://dx.doi.org/10.5772/intechopen.97830*

**4.1 Knowledge sharing and project' phases**

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

**4. Results**

important.

*Managing Inter-Organizational Knowledge Sharing: Integrating Macro, Meso and Micro... DOI: http://dx.doi.org/10.5772/intechopen.97830*
