Research objectives in theory-testing research

In order to check whether replication theory-testing research is appro- priate the following questions could be raised: ■ Do relevant persons usually experts, but sometimes practi- tioners agree on what exactly is the topic about which theory should be further developed? ■ Which core propositions of the theory have not been suffi- ciently tested in replication studies? ■ What exactly is the aim of the replication? Is it a test to see whether outcomes of earlier tests can be reproduced increase robustness of the theory? Is it a further investiga- tion of the generalizability of the proposition by exploring the boundaries of the domain to which the proposition can be extended or must be restricted? If the answers to such questions are conclusive, replication theory- testing research needs to be designed and conducted. Then the specific research objective can be formulated as follows: The objective of this study is to contribute to the development of theory T {specify the object of study} by re-testing the following existing propositions P: ■ {specify proposition P1} ■ {specify proposition P2} ■ {… etc.}; in order to {specify the aim of the replication}.

4.2 Specifying propositions in theory-testing research

In our general discussion of theory in Chapter 3, we use the word proposition to designate a statement about the relation between con- cepts . A proposition, therefore, belongs to the realm of the theory. We use the term hypothesis in the context of a study. A hypothesis is a statement about a relation between variables, representing concepts, in the instances studied. A hypothesis, thus, belongs to the realm of the empirical situation in which the proposition represented by this hypothesis is tested. Many propositions in business research have the form “A results in B” or “A contributes to B” or “A affects B”, etc. in which A is, for instance, something that a manager can or cannot do or can do to a larger or lesser degree and B is the desired result of that action. If the topic of the research is “critical success factors of innovation projects” then a proposition regarding innovation projects could be that “factor A results in success B” where A may be top management commitment and B is successful financial performance. There is a probabilistic and a deterministic way of expressing “A results in B”. These two ways are fundamentally different and repre- sent two different theories about the effect of A on B. In a theory- testing research project, the assumed relationship between A and B needs to be specified precisely in the proposition before we can deter- mine which research strategy fits best. In this book we make a distinction between three types of determin- istic proposition and one type of probabilistic proposition. Within the category of deterministic propositions we distinguish: ■ propositions that express that concept A is a sufficient condi- tion for concept B; ■ propositions that express that concept A is a necessary condi- tion for concept B; ■ propositions that express a deterministic relation between concept A and concept B. Within the category of probabilistic propositions we have the following type of propositions: ■ propositions that express a probabilistic relation between con- cept A and concept B. In business research, the proposition “A results in B” is usually impli- citly considered as a probabilistic relation: if there is more A, then it is likely that there is more B. A corresponding hypothesis would predict that for higher levels of the value of A the average level of the value of B would be higher. In terms of the example above, the hypothesis would predict that in a group of innovation projects selected for the study, the average success of Table 4.1 Correspondence between theoretical terms and theory-oriented research terms Theory Theory-oriented research Propositions Hypotheses Concepts Variables