Research Hypotheses

The following section briefly reviews the five research themes presented at the end of the literature review (see Section 2.6) and introduces several research hypotheses for each theme. These hypotheses were formulated by the researcher after extensively immersing himself in the current literature on design thinking. Each hypothesis was built on a theoretical or empirical gap in the current body of knowledge. It is the intention of the researcher to propose a contribution to knowledge by offering methodologically sound evidence to narrow these theoretical gaps.

The hypotheses are being presented in five groups, corresponding to the five larger research themes. The hypothesis statements helped to direct the data exploration and analysis. To simplify this analysis chapter, the

null-hypothesis (Hn) for each alternative hypothesis (Ha) is not explicitly stated (Adams et al., 2007). For each stated hypothesis it can therefore be assumed that the null-hypothesis states that there was no significant effect.

Each hypothesis was devised to be testable, falsifiable, and verifiable by other researchers (Lorz et al., 2013).

Theme 1: Team Diversity

The first theme looked at how different degrees of team diversity affect the application of design thinking.

Many different authors have argued that design thinking is a multidisciplinary innovation methodology (see Section 2.2.4). Design thinking teams should therefore incorporate team members from various disciplinary backgrounds.

Overall, this was expected to improve possible outcomes of design thinking project.

Hypothesis 1a: Multidisciplinary design thinking teams achieve a better final performance than single-discipline teams.

Subsequently, the argument for team diversity was extended to include other measures of diversity, such as personality traits (see Section 2.5). Analogous to the previous hypothesis, teams with a high degree of diversity of

personality traits were expected to enrich design thinking activities with many different points of view. This was expected to result in better project

outcomes.

Hypothesis 1b: Design thinking teams with a high degree of diversity of personality traits achieve a better final performance than those teams with a low degree of diversity.

Theme 2: Iteration

The second theme examined how different design thinking teams incorporate the concept of iteration into their projects. For the purpose of this study, iteration has been conceptualised as recursive movement in the design thinking process.

It has previously been argued that, multidisciplinary teams are expected to more deeply engage with the problems and choices faced in design thinking projects. Multidisciplinary teams construct a rich shared mental model, which in turn results in more diverse points of view and a deeper reflective practice of design thinking (see Section 2.5). It was therefore expected that a more iterative approach concerning the several connected activities within the design thinking process is needed to explore and reconcile these multiple perspectives (see Section 2.2.6).

Hypothesis 2a: Multidisciplinary design thinking teams iterate more than single-discipline teams.

Design thinking is generally described as an iterative methodology, despite existing linear formulations of the design thinking process (see Section 2.2.6).

Over time, individuals are expected to grow more confident in the application of design thinking and develop are more elaborate and intuitive

problem-solving strategies (see Section 2.2.7 and Section 2.2.10). It was therefore assumed that through experience, individuals are better able to appreciate iteration as a feedback and learning mechanism for their projects.

Hypothesis 2b: More experienced design thinking team iterate more than novice teams.

The concept of iteration is highlighted in multiple key publications on design thinking. It is described as an elementary principle of formalised design thinking process models (see Section 2.2.6). It was therefore assumed that the more a team iterates within a design thinking projects, the better it performs.

Hypothesis 2c: More iteration during a design thinking project leads to a better final performance.

Theme 3: Learning Styles

The third theme explored how different learning styles influence teams during the different phases of the design thinking process.

In Kolb’s experiential learning styles model, individuals are expected to (repeatedly) cycle through four different modes of learning (see Section 2.4).

Beckman and Barry (2007) have argued that there appear to be many

similarities between how individuals learn through experience (ELT) and how design thinking projects are sequenced. It was therefore hypothesised that individuals in design thinking projects cycle through Kolb’s learning styles in the suggested sequential order.

Hypothesis 3a: Each member of a design thinking team cycles through Kolb’s learning styles during a project.

Experiential Learning Theory (ELT), and specifically Kolb’s learning styles theory, argues that the utilisation of multiple learning styles leads to deeper learning, a quality also needed for successful design thinking innovation projects (Beckman & Barry, 2007). Achieving a balance of learning styles throughout a project, allows teams to constantly evaluate available

information from multiple perspectives and potentially make better decisions.

Hence, the author argued that this also influences the outcome of design thinking projects.

Hypothesis 3b: Design thinking teams which demonstrate a balance of the four Kolb learning styles achieve a better final performance than those teams who do not.

Theme 4: Perceived Effectiveness and Ease

The fourth theme studied the instances when individuals in design thinking teams feel effective and at ease during a project.

In his popular book on design thinking, Brown (2009) theoretically posits that creative confidence follows a U-shape throughout a project, with confidence being high at the beginning, declining as the team struggles to discover insights and increasing again towards the end (see Section 2.2.7). The author posited that how effective and how at ease one feels in the application of design thinking are two specific facets of the concept of creative

confidence. Both variables were therefore expected to develop in a similar pattern.

Hypothesis 4a: Perceived effectiveness and ease follows a U-shape throughout a project.

Creative confidence and informed intuition in the application of design thinking develop over time (see Section 2.2.7). Hence, the author

hypothesised that once these qualities are developed to a certain extent, they can be transferred to new projects and teams.

Hypothesis 4b: An individual’s perceived effectiveness and ease in the application of design thinking carries over to new projects and teams.

In Section 2.2.11, it has been argued that the development of creative

confidence is one of the most fundamental goals of design thinking education.

Developing creative confidence allows innovators to trust their own

problem-solving abilities and enables them to feel more comfortable with the inherent uncertainty and ambiguity of wicked problems in design thinking (see Section 2.2.7). It was therefore expected that higher levels of creative confidence within a team, and therefore higher levels of perceived

effectiveness and ease, positively influence the outcome of design thinking activities.

Hypotheses 4c: Teams comprised of individuals with high levels of perceived effectiveness and ease achieve a better final performance.

Theme 5: Teams as Networks

The fifth theme investigated what patterns of communication are beneficial to design thinking teams from a network perspective. Social network analysis was used in the exploration of this theme. As Zenk et al. (2010) point out, most studies on networks and performance focus either on individuals or the organisational level. The exploration of this research theme was therefore focused on innovation teams as the unit of analysis.

The process of design thinking is best thought of as a set of connected activities (Brown, 2009). Each of these activities favours a slightly different skill-set. Based on their experience, Beckman and Barry (2007) suggest that good groups rotate leadership positions and specific roles within a team based on each team member’s skill-set. When analysing design thinking team structures from a social network perspective, it was therefore expected that how important an individual is to his/her group changes throughout a design thinking project. Building on social network theory, individual

importance within a team was conceptualised as a ranking order based on individual eigenvector centrality scores.

Hypothesis 5a: The relative importance of individuals changes throughout a design thinking project.

Team cohesion is seen as a precondition to functioning innovation teams as it leads to more exploratory behaviour (Hülsheger et al., 2009). Radical collaboration and the frequent exchange of ideas and insights are thought to be one of the principles of design thinking (see Section 2.2.5). Teams who excel in both these behaviours were therefore expected to achieve superior performance in design thinking projects.

Hypothesis 5b: Design thinking teams with a high degree of internal cohesion achieve a better final performance than teams with a low degree of internal cohesion.

Similar to the previous Hypothesis 5b, radical collaboration and the frequent exchanges of ideas beyond one’s own team were expected to enrich and inform the decision made within a team (see Section 2.2.5). External cohesion generally enables a design thinking team to benefit from outside perspectives and expertise. This allows a team to enrich its reflective practice and improve its internal decision-making. Teams with high external cohesion were therefore expected to achieve superior performance in design thinking projects.

Hypothesis 5c: Design thinking teams with a high degree of external cohesion achieve a better final performance than teams with a low degree of external interaction.

The five presented research themes and the corresponding 13 research hypotheses are further explored in the quantitative research study presented in Chapter 4. A visual summary of the themes and hypothesis is provided in the following Figure 3.2.

Figure 3.2: Summary of Research Hypotheses