Conceptualisation Methods

In section 5.3.1 categories are dierentiated from each other. In this section the way in which individual components of the data are linked together into a broad conceptual framework is investigated. This approach enables the re-searcher to identify the relevant phenomena in a complex system that is more

than the sum of its parts (Denzin and Lincoln, 2011).

The strategies presented in section 3.2.2.2 are not mutually exclusive and some strategies are similar. The applicability of each strategy (section 3.2.2.2) is con-sidered by investigating which strategy is used for which type(s) of data and outcome, until the nal combination of conceptualisation strategies to be used is identied. The three strategies identied to conceptualise the data are; the links exploration, x-ray view and social domains strategies (Hennink , 2011).

Exploring Links is a strategy that entails identifying links that exist in the data that could be followed up on. These links are identied in an incre-mental manner to develop a comprehensive understanding of the network of relationships in the data. The X-Ray View strategy is applicable to identify the backbone of structural aspects of the data, which in this case is the core barriers of eective communication. The Exploring Links strategy and the X-Ray View strategy both served as building blocks to develop the conceptu-alised COMMPAS model by means of the Social Domains strategy and to fur-ther construct the COMMPAS Model. The Social Domains strategy addresses seemingly unrelated issues that collectively become an important component in the data, even though they seem insignicant when isolated. The Social Domains strategy is the primary method used to develop the conceptualised COMMPAS model.

5.3.2.1 Exploring Links Method

A network diagram is developed to explore the links between the codes (g-ure 5.5). The development of the network is based on the SNA methodology (chapter 2). Each code represents an actor, and the lines that connect the codes represent the relational ties along which resources are transferred. Dur-ing the description and categorisation phase, several associations are observed among the data. These associations will be investigated for possible links.

While developing the links, the dyads (pairs of actors and their associated ties) and triads (a subset of three actors) became evident and highlights in which orientation the relationships are linked. For example, a triad exists be-tween lack of experience, interdependent and update, but also bebe-tween lack of experience, interdependent and lack of knowledge.

An investigation of these sets produce no meaningful information and some of the triads, such as Role Denition-Update-Interdependent, do not consti-tute meaningful relationships that produce new insights into the data. Some of the triads reect connections between codes that are, at this point of the research, obvious to the researcher, which makes this method of conceptualis-ing ineectual.

Figure 5.5: Exploring links between codes.

The Exploring Links method is found to be confusing, inadequate and lim-ited as it is one-dimensional. More context lies behind each issue that is not reected in the network, which produces inaccurate information. Even though the Exploring Links method was ineective, it was useful in exploring how integrated the codes are and how they inuence each other.

The codes are a single concept that represents a large group of complex is-sues relevant to context. An attribute is a clear and specic characteristic that is not linked to a certain context, but is used to describe a more complex place, person or thing. The attributes are listed next to the codes to investi-gate if each code, based on the context from which it is developed, could be linked to an attribute. Some links are clear, while other links require a more abstract approach. The results are illustrated in gure 5.6 and explained in section 5.3.2.3.

Figure 5.6: Exploring Links between attributes and codes.

5.3.2.2 X-Ray View Method

Taking an x-ray view is done by looking past the detail of the data and by asking what the central components that hold the data together are. Thus, complex data results in a critical investigation and looking past the detail of the data.

After looking past the detail of the data, three core components emerged.

First, communication deciencies are rooted in human error and not in techni-cal issues or in the lack of technology. Most of the issues stem from some kind of lack of knowledge, whether it is the lack of knowledge of how to commu-nicate, how much information to communicate or with whom to communicate.

The second factor is that employees take up the seriousness of their man-ager regarding feedback and communication. In divisions where the manman-ager is serious about constant communication, keeping everybody up to date and sending feedback, the employees are more likely to take it seriously. The op-posite is also true: if managers are not serious about sending feedback or constantly communicating with other stakeholders, the chances that employ-ees, especially contractors who do not enjoy administrative responsibilities, will take it seriously are small.

The greatest component that emerged was the lack of a shared culture of com-munication, where role players in the communication system are constantly keeping each other informed. This component was raised from examples of

sub-groups that share such a culture and experienced less internal communi-cation issues.

5.3.2.3 Social Domains Method

The Social Domains method is based on the results of the Exploring Links method. As attributes are not restrained by context, it is simpler to group attributes into categories that will be used to categorise the developed codes.

The development of attributes is rooted in the data and codes are linked to attributes based on the context that the codes are developed from. Developing categories based on attributes and grouping the codes into categories based on their associated attributes, is thus a valid process. The categorisation of attributes forms part of the conceptual model and is a preparation step for accurately linking the codes to the conceptual domains, as shown in gure 5.8.

The nal conceptual model is introduced in gure 5.7.

Figure 5.7: Conceptual Model.

Conceptualising the Social Domains is done by investigating categories (sec-tion 5.3.1), to devise higher-order categories from the data (Hennink , 2011).

By means of the Social Domains method, the categories in gure 5.4 are fur-ther developed into three concepts, namely Cognitive, Connective and Strate-gic. This is the foundation on which the COMMPAS model is built. The construction of the COMMPAS model follows.