Choice of empirical setting

As argued in previous sections, this study is designed to conduct theory testing of a casual model. In theory testing of casual models, internal validity and statistical conclusive validity are ranked more important than external validity (Cook and Campbell 1979). Hence, the chosen empirical setting should provide sufficient variation in the main variables included in the theoretical model, and all other variables should ideally be constant, that is, no variation.

However, this is hardly the case in any real life empirical setting, thus some “noise” must be expected. For instance, a highly heterogenic sample will provide the necessary variation in the variables in the model, but it will also induce noise into the results due to variation on variables outside the model. The researcher needs to balance this tradeoff, as accounted for in the

subsequent paragraph. In order to secure a high level of internal and statistical conclusive

validity, one industry, opposed to many industries, is particularly suitable. Selecting one industry will ensure that the projects are (more or less) homogeneous and thereby secure a higher level of internal validity (i.e., it should be possible to isolate third variables), and secure statistical conclusive validity (i.e., less random error variance), (Cook and Campbell 1979). In short, we presume that the choice of one industry, as in the empirical setting, will exclude or reduce confounding factors associated with a specific industry. In other words, external validity is sacrificed in order to achieve the highest possible level of internal validity, which is critical when conducting theory testing. If the theory holds in the sample (i.e., the theory is not falsified), further studies should test for external validity by performing additional studies in other contexts.

However, although only one industry has been chosen, there will be differences between the projects in the sample. The contractor industry is highly heterogenic and operates in all segments of the market, for example within design, fabrication and installation, research and development, engineering services/consulting, and software development etc. Although we have selected one industry as the empirical setting and thus reduced external validity, the study includes a broad selection of innovation projects, different contractors, and different oil companies. Altogether, 19 oil companies and 98 contractors are represented in the final sample of the study. Hence, due to the heterogeneous projects, contractors, and oil companies, we are confident that there will be sufficient variation in the main variables in the research model.

The theories applied in the study to analyze governance of innovation projects are generic.

Hence, they should be valid for all the projects analyzed. However, since different segments of the industry are included in the study, for example, research and development, design and construction, and software development, the innovation projects are not homogeneous. Ideally, one segment or one project type should be analyzed to reduce noise. However, all segments were included in the study to secure an optimal sample size. Hence, the need for a homogeneous setting was sacrificed in order to increase the sample size and thus statistical power.

The requirements of the empirical setting are fulfilled if the variables in the theoretical (or conceptual) model materialize in the empirical setting to varying degrees (Troye 1994). In short, the researcher must choose an empirical setting where the phenomenon of interest actually appears. In this paragraph, we argue that the main constructs in the theoretical model are present in the industry, and that they are present to varying degrees in the sample. Below we briefly account for the relevant variables.

Historically, the Norwegian petroleum industry has been heavily influenced by the American business culture. American companies were the first to operate on the NCS (e.g., Conoco Phillips, ExxonMobile), and they brought with them the rather tough and formal American contract style. Contracts were viewed as crucial, and considerable resources were spent in developing comprehensive and exhaustive contracts. Because of this foreign influence, the industry developed a more formalized culture than other Norwegian industry clusters. In short, extensive use of formal contracts should be expected.³³

The extensive use of formal contracts in this industry might affect the level and presence of other more informal governance mechanisms; that is, a substitution effect might be present. Would the extensive use of formal contracts totally replace trust and cooperative norms for example? The NORSOK initiative had earlier indicated that these aspects were poorly developed between the parties in the industry (NORSOK 1995). Hence, we conducted in-depth interviews to make sure that these dimensions or constructs were present. Fortunately, the interviews revealed a strong presence of trust and relational norms in the industry, that is, the presence of ‘relational

33Compared to other industries a ’one‘ on the Likert-scale would indicate little formalization. The scale is relative, and a ‘one’ in the petroleum industry does not necessarily mean the same as a one in other industries. This is mainly due to the history of the industry. To avoid problems with the scale, the choice of one industry seems reasonable.

Formalization is certainly different in construction and R&D projects, but we chose to include both project types.

Both project types are important in this industry, and they are both relevant in the study of value creation and innovation.

contracts’ between the parties. Furthermore, these attitudes and behaviours were regarded as fundamental in achieving superior project performance by the parties. Moreover, the length of the projects in the sample indicates that cooperative norms could be developed (project length;

MEAN=2 years). To conclude, we presume that relational contracts are present to a varying degree in the projects of interest.

Project specific investment is a critical variable in the theoretical model. Investments in these assets are hypothesized to positively affect the relevant performance effects in the study. It is of critical importance that specific investments are likely to exist in the projects or dyads to a varying degree (Troye 1994). Below we argue the presence of these investments, first, on the customer side, and second, on the contractor side.

The oil companies on the NCS are generally reluctant to make specific investments in a

relationship. They are anxious about being ‘caught’ in a situation where they are 'locked in' and dependent on just one contractor. This attitude was confirmed by the contractor companies in the interviews and in several interviews with informants in Hydro. The oil companies put a lot of effort into establishing and maintaining a well functioning market. Long-term relationships are 'broken' and new contractors are invited to compete on a regular basis. To sum up, transaction specific investments on the customer side are presumed to be present only to a marginal degree.

As argued in Chapter 1, it is reasonable to presume that the contractors invest in generic and specific assets related to the execution of an innovation project. The logic is straightforward. To create value, develop new technology, new solutions and so forth, investment is necessary in knowledge, training, new equipment etc. Some of these investments are likely to be project specific. During the preliminary interviews, we asked the informants if specific investments were present in the projects they had conducted. The response indicated that several contractors had made specific investments in for example: organization (e.g., adjusting the organization to the specific project), special training and education, specific equipment, and time (getting to know the customer organization and their problems etc). The interviews and the types of work performed in the sample project indicated that project specific investments are present to some degree – and that these investments are most likely to be found on the contractor side of the dyad.

In conclusion, we argue that the empirical setting chosen is likely to contain all of the relevant variables in the theoretical model. Further, the critical variables are likely to exist to a varying

degree in the sample. These conclusions were drawn on the basis of preliminary interviews and novel insight into the industry structure. Hence, we conclude that the empirical setting is relevant for the test of the theoretical model. The choice of one industry as the empirical setting will exclude or reduce confounding factors associated with a specific industry. External validity was sacrificed in order to achieve the highest possible level of internal validity, which is critical when conducting theory testing. The empirical setting is homogenous, although the contractor

companies operated in different market segments. To sum up, we presume that the choice of empirical setting will secure enough variation in the independent constructs.