The testing of propositions 1b, and 2b in incremental innovation projects see Table 5.2 can illustrate the advantage of the parallel
single case study. The corresponding hypotheses predict not new part- ners, and similar technical capabilities in these projects. If it is assumed
that in a serial case study, case 6 would have been selected for the first test, the test would have confirmed the two hypotheses. After this first
confirmation, a second case would have been selected for replication.
The replication strategy after a confirmation could be to select a case from a very different part of the domain from which the theory is
considered applicable. Then the new case in a serial case study would not have been a case from Nokia, but a case from, for example, another
economic sector. This would continue until cases were found that were rejected, and then the boundaries of the domain to which the theory
applies would be determined.
However, by using the parallel case study, rejections of hypothesis 1b were found immediately, indicating that proposition 1b for the small
domain of the Nokia cases cannot be supported. The parallel single case study, thus, appears to be an effective and relatively fast way to dis-
cover cases in which the proposition is not supported.
The replication strategy, after a confirmation, could also be to select a case from the same part of the domain: the new case in a serial case study
would be another case from Nokia. Then, after the second test say case 7 or third test say case 8, the conclusion would be justified that
proposition 1b could not be supported for Nokia cases, and replications with cases 9 and 10 would not have been needed. This illustrates the dis-
advantage of the parallel single case study approach, i.e. the potential to waste time and effort on measurement and hypothesis-testing.
The danger of the parallel case study can be illustrated with the results of testing propositions 1a and 3a with respect to radical innov-
ation projects see Table 5.1. The test result of case 3 is enough to conclude that proposition 1a which formulates a deterministic rela-
tion is not correct, and the test result in case 4 is enough to conclude the same regarding proposition 3a. The danger is that inspection of all
five tests together results in conclusions such as “but … the hypothesis is confirmed in the large majority of cases four out of five”. Such a
conclusion could only be made after many replications when the hypothesis is rejected in only one case but is confirmed in all other
cases, and if one accepts a “pragmatic determinism” view. Normally, a rejection of the hypothesis in a single case from the domain to which
the theory is assumed to be applicable is sufficient to reject the hypothesis for that domain although it might be true for a smaller
domain.
The fact that the hypothesis could be confirmed in the majority of tests but that there are also instances in which the hypothesis was
rejected can also be an indication of the correctness of another propos- ition, a probabilistic one.
5.3.4 Candidate cases
The domain covered by the theory is the universe of all instances of innovation projects in which radical and incremental innovation was
pursued, without restrictions in terms of geography, economic sector, time, etc. It was enough for this initial test of new propositions to find
a single innovation project for each of two types of product innov- ation that was successful in the absence of the conditions specified by
the propositions, and this could be a project from any company and in any sector.
Cases were selected from the CGCP database. The advantage of using this database was that it is not only a partial list of instances of
the object of study from which cases can be selected but also contains the data that are needed for the testing. It was a commendable strategy
to test the propositions in this database initially and, after a series of replications, to draw conclusions regarding the support or non-
support of these or altered propositions for the sub-domain of instances in this database. In a next series of replications, these con-
clusions could be tested in instances of the object of study that are not covered by the database.
5.3.5 Case selection
Because a new proposition must be tested, any instance will do for a first test. It could be a project from any company and in any sector.
Therefore the Nokia cases selected were as good for this purpose as innovation projects undertaken by any other company. This reasoning,
however, applies to the first case in a serial case study. A second case and later cases of the series could be selected on the basis of a replication strat-
egy that is based on the test result in the preceding case.
The selected cases should be instances of either a radical or an incre- mental innovation project. An innovation project was categorized as rad-
ical if both the technology and the market were new, and an innovation was considered to be an incremental one if both the technology
was already available and the market was current. It should be specified how in the set of candidate cases, differences between new and already
available technology, and between new and current markets could be recognized.
Because the propositions in this study specified necessary conditions, successful cases were selected selection on the presence of the
dependent concept, i.e. projects that had resulted in the market launch of a new product. Product launch was identified through press
releases.
5.3.6 Hypothesis
Because the propositions in this study specified necessary conditions and the selection was done on the basis of the presence of the depend-
ent concept, the hypothesis was that the condition was present in each case that was studied.
5.3.7 Measurement
In order to test the hypotheses, the three collaboration characteristics collaboration history, technological capabilities, and level of commit-
ment had to be measured in each case.
A partner in an alliance was considered to be a not new partner for Nokia if that partner had collaborated with Nokia in a previous
alliance in the database since 1985 and new if it had not collaborated before. The year 1985 was arbitrary and it is possible that partners that
had collaborated with Nokia before 1985 were incorrectly classified as new. This measurement procedure was precisely specified and, there-
fore, likely to result in reliable scores.
A partner’s technological capabilities were mainly determined by its code in the SIC. Partners with the same code were considered to have
similar technological capabilities, whereas partners with other codes were considered to have different capabilities. An industrial classifica-
tion such as SIC is not a classification of technological capabilities and the measurement validity of this operationalization of similarity in
capabilities, therefore, depends on the likelihood that companies with the same capabilities get the same SIC code. It is unknown whether or
not companies with the same capabilities do indeed have the same SIC code. This method for measuring similarity of technological capabilities
