Abstract

Specialisation, by seeking theoretically deeper explanations or more accurate predictions, is common in the sciences. It typically involves splitting, where one model is further divided into several or even hundreds of narrow-scope models. The Information Systems (IS) literature does not discuss such splitting. On the contrary, many seminal IS studies report that a narrow scope is less strong, less interesting, or less useful than a wider scope. In this commentary, we want to raise the awareness of the IS community that in modern scientific progress, specialisation – an activity that generally narrows the scope and decreases the generalisability of a hypothesis – is important. The philosophy of science discusses such positive developments as splitting and trading off a wide scope in favour of accuracy. Narrowing the scope may increase value, especially in sciences where practical applicability is valued. If the IS community generally prefers a wider scope, then we run the risk of not having the information necessary to understand IS phenomena in detail. IS research must understand splitting, how it results in narrowing the scope, and why it is performed for exploratory or predictive reasons in variance, process, and stage models.