5.2.1 Limitations
A limiting factor of our study is the Cronbach’s alpha, which is relatively low for each variable. This means that the reliability of our research is low and can confirms that the results do not show what they should show. This could be caused by the limited number of N, which is 38. Peduzzi et al.(1996) have published simulations studies suggesting that logistic and survival models will produce
reasonably stable estimates when the limiting sample size allows a ratio of approximately 10 to 15 observations per predictor. Within this study the number of predictors, or independent variables, is 5. This means that the minimum number of respondents must be 50. Our respondents number of 38 is lower than this 50. When this is the case you do not know whether the relationships described are real relationships or that the relations I described as non-existent don’t really exist. To solve this problem partly I have measured the relationship between radical innovative capability and radical innovation outcomes once during the regression analyses and have removed the variable radical innovative outcomes during the other six regression analyses. By taking this step our reliability improved somewhat, because the number of independent variables decreased from 5 to 4. This indicated that 40 respondents was enough. Our respondent number of 38 is close to this 40. Another aspect to discuss is the striking significant relation between team climate and support leadership (p < 0,05). Regardless of the direction of the arrow the standard regression weight between support leadership and team climate will be 0.669. So, hypotheses 5a and 5b show exactly the same values and exactly the same relationship, while managers expected that hypothesis 5a really existed and that hypothesis 5b probably did not exist. After having divided employees and R&D managers into groups, the correlation and regression measured within the employee group was the same for hypotheses 5a and 5b. The correlation and regression measured within the manager group was the same for hypotheses 5a and 5b. When looking at the data of the employees the relationship between team climate and support leadership was significant. But when looking at the data of the managers the relationship between team climate and support leadership wasn’t significant. So, the limiting factors related to this are the fact that hypothesis 5a and hypothesis 5b show exactly the same values each time. I have no clear explanation for this. Another limiting factor related to this is the fact that the relationship between team climate and support leadership isn’t significant when looking at the manager data.
Another limiting factor of this research is the fact that hypothesis 3 isn’t significant. Hypothesis 3 isn’t supported, but based on the fact that the fact that the hypothesis isn’t significant, we don’t know for sure if this is caused by the extremely high value of teamwork cohesion or by the fact that the relationship isn’t significant.
5.2.2 Further research
It is very well possible that some follow-up studies based on this research will take place in the future.
Firstly, a follow up study could attempt to improve the reliability (the Cronbach alpha) of this research. This can be done by carrying out the study on a larger scale and collect more data. When this happens, the N value of the research can be increased and the reliability should therefore improve.
Another second potentially interesting follow – up study may look more specially at the variable teamwork cohesion. When this variable is high valued within your company it will have a negative influence on team learning. As described by Zolin, Kuckertz & Kautonen (2010) an entrepreneurial team performs better if the team members are willing to modify their roles and also leave the team if required. Further research could try to map how to reach this. The optimal teamwork cohesion and how companies could achieve this optimal teamwork cohesion is an important aspect to look at. It is a challenge for a manager to create an optimal teamwork cohesion which isn’t too high on the one hand and on the other hand ensures that the team climate is at a good level.
A third follow up study could deepen the relation between team climate and support leadership. As described above, it is striking that the influence of team climate on teamwork cohesion is exactly the same as the influence of support leadership on team climate. The standardized regression weight of the influence from team climate on support leadership is exactly the same as the standardized regression weight of the influence from support leadership on team climate. This value is 0,669. After having divided, the data I conducted into groups, I concluded that the relationship is much more present at the employee data and has been observed very limited at the managers data. A striking point is that also after having divided the data in the groups of employees and managers in both groups hypothesis 5a and hypothesis 5b show exactly the same correlations and regression weights. A follow up study can look at the cause of the fact that these correlations and standardized
regression weights are exactly the same, while managers in the interviews on the one hand suppose that the influence of support leadership on team climate really exists and on the other hand have doubts about the influence of team climate on support leadership. Based on the fact that the quantitative data and the qualitative data divers on this point it is very interesting to look at it more detailed.