Methods for Data Collection: Mixed Methods

This section will focus on the procedural steps that aimed to categorize the network actors, the content of their knowledge acquisition motives and goals, their roles within the network, who they frequently connected with whom, and how they communicated (Carringion & Scott, 2012). SNA is most benefited from robust data collection, as the outset of a social network investigation requires rich descriptions of the relational patterns before further analysis can commence (Hanneman & Riddle, 2005). Defining these features of a network structure aids researchers to understand concepts such as the density of social relations and the ease at which individuals work together (Hanneman & Riddle, 2005) to enable an understanding of how opportunities or constraints may emerge in the social structure (Granovetter, 1985, Burt, 1992; Adler and Kwon, 2002). The data collection techniques were designed to fully immerse the researcher in understanding the functional elements of the whole network and the mechanisms that drive innovation performance.

3.6.1 Qualitative Methods for Data Collection

Portions of this investigation focused on qualitative data collection techniques, which would allow for a deeper appreciation of the contextual factors that might not be immediately evident through a quantitative investigation alone (Silverman, 1993; 2015; Miles & Huberman, 1994). The volume of events and data collection opportunities was extensive, and the researcher needed to use judgement to appropriately define the level of involvement that was possible. However, the researcher must obtain rich data sets from a variety of sources (Hanneman & Riddle, 2005; Wasserman & Faust, 1994). This required the researcher to adopt

106 a level of flexibility to ensure that data collection was robust but this also provided the benefit of reflexivity in the research process. This enabled an iterative and recursive approach to pursuing field experiences based on access and development within the relationship. This is important when the body of theory and literature on how relations might work successfully is largely fragmented (e.g. Andersen & Christensen, 2005).

The aim was to capture complete descriptions of the topic being studied and the contextual conditions that may not be evident from a solely quantitative analysis and to facilitate an unbiased emergence of relevant constructs, as well as aid in identifying casual links between constructs and antecedents that contribute to the performance of this collaboration for the subsequent phase of the investigation (Miles & Huberman, 1994, Yin, 1994). Studies that seek to characterise the differences in how well connected an individual is within a network is consequential for understanding the opportunities (and constraints) that are available within the network. The study is set within an active network, which provided many opportunities to collect data during periods of dynamic change (Castilla, 2007; Yin, 1994). This form of investigation enabled the researcher to delve deeply and intensively into the phenomenon of interest in its natural setting (Burns, 2000), helping to reveal additional factors not originally included in the theory (Eisenhardt, 1989). The researcher adopts a subjective stance and unavoidably serves as an instrument in the research design as objective and external instruments cannot reveal or aid in inferences about the behaviours observed or the contextual conditions of the conversations held with participants (Spradley, 1979). Through studying the contextual conditions that influence “the meaning that people attribute to the “real world conditions” and allows the story to unfold in its own way (Yin, 1994: 4). The extensive collection of qualitative data that was collected allowed the researcher to begin to develop the descriptive phase of the research. This allowed the researcher to plot a socio-gram of task interdependence utilizing the connections that emerged from the varying sources of qualitative data. The archival documents and participant accounts allowed for a longitudinal lens of the development of the network over time.

3.6.2 Quantitative Methods of Data Collection

Quantitative techniques are applied to further characterise and measure such things as the intensity of interactions across the range of relational linkages, the level of cohesiveness or cluster ability that is derived from the qualitatively focused aspects of the investigation. This collection technique might focus on deriving scaled measures to indicate intensity or the degree of reciprocation. The data derived can be mathematically and graphically represented to display

107 and pinpoint specific areas of interest within the overarching network structure. Networks with few connections lack in solidarity and tend to fall apart (Hanneman & Riddle, 2005). However, Burt (1995) argues that these weak connections (also known as structural holes) provide the network for novel information. Software systems UCINET, Pajek, and Netwdraw was employed for a portion of the network that were clearly identified based on the actor’s obligatory relational ties. In addition, the cross-sectional survey collected several independent observations to give greater depth to the node (actor) compositional elements and to develop descriptive statistics.

3.6.3 Ethical Compliance and Research Integrity

Prior to the beginning of the investigation, considerations were made towards ethical compliance, which pose significant challenges for network researchers. Research involving human subjects within the social sciences typically follows ethical compliance and in which anonymity is guaranteed. Additionally, these studies focus on large scale data collection or generalizability to larger populations, which also aids in the task of ensuring anonymity (Kadushin, 2011). The network analyst differs in respect to what they seek to collect information; such as who relates to whom and how. This approach reveals variances within the network structure that might have implications for those that know where certain network members sit within the organization (Borgatti & Molina, 2003; Moreno, 1938). This potential issue was addressed by including all members of the network in the analysis to create a level scale for anonymity. Additionally, actors were assigned anonymous identification codes in the data reduction phase. The researcher is the only person with access to the master database.

The confidentially of the network was addressed in the format of the anonymization process. This umbrella master agreement required that strategically sensitive would be reviewed by the industrial sponsors prior to publishing to ensure that strategically sensitive information was not revealed. Additionally, research ethics had been considered and consent was granted in accordance with the Durham University published research ethical guidance, which is aligned with the British Psychological Association guidelines. (Please see appendix for a completed flow chart and check list.)

All participants were informed of their rights, which included their ability to refuse to answer any questions, omit answers from the final transcripts, and their right to withdraw from the study at any time. They were provided with a project information sheet, which included details of the study and the ongoing opportunity to refuse consent. The benefits of the study

108 emphasised the contribution to the collectively in which their answers would allow the relationship to be enhanced (Kadushin, 2011). (Appendix 1)

Interviews were audio recorded and later transcribed. Observations were not audio recorded, however field notes were taken and later transferred to a digital format to be stored in the study’s database. Documents were also labelled and stored in a similar format. During data reduction, evidence was summarized, anonymized, and compiled into a database for coding and theme identification. Participants in the survey data collection phase were provided with an overview of the research study and informed consent prior to initiating a response (Appendix 2). Data was collected electronically via Qualtrics and each participant was assigned anonymous ID code, identifiable only by the primary researcher. The next section of the chapter will discuss the units collected for analysis, which employs a holistic view of a single case study as well as the appropriateness of this technique.