Deterministic relation Probabilistic relation

assumption that there is a deterministic relation between team size and success which could be formulated as “Team size seven and up is suffi- cient for success” and “Team size lower than six is sufficient for lack of success”. The trend in this data matrix can be formulated as follows: Proposition 3a: The larger the team size, the more likely the success of an innovation project. Table 9.5 supports the existence of a probabilistic relation between the independent concept management commitment and the dependent concept success. However, such a proposition would not add much to propositions 1a and 1b. Similarly, probabilistic relations between infra- structure and success and between investment and success that could be proposed do not add much to propositions 2a and 2b. These examples demonstrate how statistical tests in surveys, which suggest probabilistic relations, could easily hide factually existing deterministic relations. This is the reason why one always needs to look first for deterministic relations in theory-building research, before looking for probabilistic relations.

9.1.9 Outcome

The likely outcome of the discussed analytic procedures consists of one or more propositions. If the relationship between the concepts A and B in the data matrix is more or less random, the study has failed to gen- erate propositions. If this is the case, another perhaps more intensive Table 9.5 Data matrix regarding management commitment Management Success commitment Case 1 H Y Case 2 H Y Case 3 H Y Case 4 H Y Case 5 M Y Case 6 M N Case 7 M N Case 9 M N Case 8 L N Case 10 L N exploration might be attempted, which might result in other candi- date concepts and hence other candidate propositions. If the analysis has been performed in an appropriate way i.e. if the procedures as described in the Chapters 5–7 for theory-testing have been applied correctly, then the resulting propositions are proven to be true in the set of selected cases from which these propositions have emerged. This implies that an initial test has been conducted and that replication studies can be designed and conducted. Box 13 Building a theory on successfully helping city government Yin 2003: 49 discusses Peter Szanton’s 1981 book Not well advised as an “excellent example of a multiple-case replication design”. This study, as presented by Yin, is not a replication study in our definition of replication but a good example of a theory- building comparative case study. Szanton studied eight cases of attempts by university groups to collaborate with city offi- cials, which all failed. Then he provides five more cases in which non-university groups failed as well. A third group of cases showed how university groups successfully helped busi- nesses, not city government. A final set of three cases was successful in helping city govern- ment. The latter three groups “were concerned with implementation and not just with the production of new ideas, leading to the major conclusion that city governments may have peculiar needs in receiving advice”. Two conclusions seem to have been formulated: 1. supporting city governments is successful if there is an implementation of the newly generated ideas; and 2. city governments have other needs than businesses. This conclusion is pre- sented by Yin as “the major one”. Neither of these two conclusions is the result of replication, because the concept of replication concerns conducting a next test after initial testing. No initial proposition was formulated in this study and no testing was conducted, so there was no instance of replication in this study. Both conclusions are the result of theory-building through a comparative case study. Proposition 1, stating that “being concerned with implementation” is a necessary con- dition for successfully helping city governments, might have been based on an inspec- tion of the data matrix of the 16 8 + 5 + 3 groups that tried to help a city government, provided that there is sufficient evidence for the absence of implementation activities in the 13 non-successful groups. Proposition 2, stating that “city governments have peculiar needs”, might have been inferred from an inspection of the data matrix of the six 3 + 3 successful groups, provided that there is sufficient evidence for the absence of imple- mentation activities in the three groups that successfully supported businesses.