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**CHAPTER 4: RESULTS**

The analytical strategy presented in the previous chapter was applied to the data in order to address the research question as to whether trusted bridging chains have a positive effect on open innovation. The results of the analysis are included in this chapter and aligned to the hypotheses. A descriptive analysis is presented at the onset, followed by a quantitative analysis. Subsequently, a fuzzy set qualitative comparative analysis (fsQCA) is presented culminating in a core and peripheral causal analysis.

** Descriptive analysis**

Table 15 (below) illustrates the different graph types that emerged from the intervention. A graph contains a number of referrals that form chain/s. More than one chain can be present in the same graph. The table also includes the number of chains per graph configuration and shows whether solutions emanated from the starter group (seed sample) or through a chain (through indirect relationships). All scores are listed on the far right. A score that contains the symbol “^{U}” next to it, means that the solution was submitted by a starter, hence not by means of a chain and therefore not by anyone who has an indirect interpersonal relationship with the focal organisation.

A chain was formed when a starter referred another individual. Therefore, as a minimum it can comprise two entities: the starter and referred individual. If a starter (the person who opted in) submitted a solution, this was derived from a direct link to the focal organisation. If a person who was referred by the starter, or referred by another referred individual, submitted a solution, then the solution was derived though a chain of referrals: hence through indirect relationships to the focal organisation.

When a circle stands alone, it means that there was no referral chain assembled and that a solution was submitted by a starter. A “0” on the referral link means that the chain was not passed forward further, while a “1” means that the chain was progressed further, beyond an initial referral.

Type 1 graphs, Table 15, related to people who opted in but did not refer someone else, so theoretically there was no referral chain. There were 121 people who opted in, of whom 77 never referred anyone else, while 44 did start a referral process.

There were 77 referrals in total, emanating from the 44 starters. Two cases had to be filtered out due to invalid data, leaving 75 valid referrals. One of the opted-in individuals did not refer another person but submitted a solution which rated the lowest solution score (see A in Table 15) of 48%. Two other starters submitted solutions but subsequently still referred someone else.

Solutions A, D and G originated from the seed sample (starters), so these solutions did not come about through indirect relationships by means of a chain. Solutions B, C, E, F, H and I came about by means of indirect interpersonal relationships to the focal organisation, through a chain.

There was only one Type 2 graph and it resulted from the starter referring just one other individual. One solution was generated from this form of chain and scored 60%.

There were nine Type 3 graphs (containing one longer chain) where the starter referred an individual and this person referred another. One of these chains scored the second highest solution score: 94%.

All the other types occurred only once. Graph Type 4 was a branch, where the starter referred two people, but the process did not produce any solutions.

Graph Type 5 comprised an initial referral, followed by a branch referral (thus two chains) and did not result in any solutions.

Graph Type 6 was particularly interesting. An individual submitted a solution which scored 78%, then referred three other people, of whom two submitted solutions rated 86% and 82% respectively. Hence, the last two scores in this case were derived from chains.

Graph Type 7 reflects the case where the starter submitted a low-scoring solution of 49% and then instigated a branch referral (more than one referral and therefore two chains), through which one of the referrals passed the chain forward

Graph Type 8 was a three-way branch referral where two chains moved forward. Person H submitted a solution but also passed it forward again by referring someone else.

In total, there were three cases where a person submitted a solution, but also passed it forward (D, G and H). Two of these individuals received the lowest scoring solutions: G with 49%; H with 59%. This might imply that they did not have confidence in their own solutions, and therefore passed the problem forward.

Solutions submitted through starters (without involving a chain) were not analysed further, as these solutions did not come about through a referral. Moreover, there was no referral data associated with these solutions to enable further analysis.

In total, from the six solutions emanating from chains, and therefore indirect interpersonal relationships to the focal organisation, five solutions came from just one indirect link (one referral); and one solution from two referrals. One individual also passed the chain on after submitting a solution. However, it appeared that the solution scores from starters (no chains), scored on average much lower than solutions derived from chains.

In summary, and before any additional analysis has been conducted, it appears that:

Chains produced more solutions (six as opposed to three), with a higher average score than solutions not derived through chains (starters).

The highest scores came about through chains.

Most solutions (in five out of six chains) resulted from just one referral.

**Quantitative analysis**

**Reliability and factor analysis**

**Dependent variables**

*Solution rating*

As discussed in the previous chapter, the CSDS instrument was used to score solutions independently by three raters.

Firstly, the consistency of scores from raters (inter-rater reliability) combined was computed where the rates were treated as items across all nine solutions, which indicated a Cronbach alpha of 83%. Secondly, the data were transposed to show the ratings per solution as cases and the items being the various questions of the CSDS instrument. There were limited missing values (4%) where averages were taken and one specific item had to be removed in totality. Across all items and cases, the reliability was 97.8%.

CHAPTER 1: INTRODUCTION

1.1 BACKGROUND .

1.2 PROBLEM STATEMENT

1.3 PURPOSE OF THE STUDY

1.4 SIGNIFICANCE OF THE STUDY

1.5 RESEARCH DESIGN

1.6 RESEARCH QUESTIONS AND HYPOTHESES

1.7 ASSUMPTIONS AND LIMITATIONS

1.8 ORGANISATION OF THE STUDY

CHAPTER 2: LITERATURE REVIEW

2.1 OVERVIEW

2.2 INNOVATION

CHAPTER 3: RESEARCH DESIGN AND METHODOLOGY

3.1 RESEARCH PHILOSOPHY

3.2 RESEARCH DESIGN

3.3 RESEARCH METHOD

CHAPTER 4: RESULTS

4.1 DESCRIPTIVE ANALYSIS

4.2 QUANTITATIVE ANALYSIS

4.3 FUZZY SET QUALITATIVE COMPARATIVE ANALYSIS

CHAPTER 5: SUMMARY, DISCUSSION, CONCLUSION AND IMPLICATIONS

5.1 SUMMARY OF THE STUDY PROBLEM AND METHODOLOGY

5.2 DISCUSSION OF RESULTS

5.3 CONCLUSION

5.4 IMPLICATIONS FOR PRACTICE

5.5 IMPLICATIONS FOR FUTURE RESEARCH

REFERENCES

APPENDICES

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