This study introduces a framework for evaluating decision models in organizations that conduct custom software development. The framework takes the form of a metamodel into which decision models can be embedded and assessed. In response to the turbulent, heterogeneous task environments facing software firms, the framework targets each model’s self-adaptive or inductive features for analysis. The evaluation mechanism is comprised of homomorphisms from abstract algebra and the transition function, observability and controllability features of control systems theory. The meta-model is tested on three candidates, two static models and a dynamic model based on Simon’s behavioral model of rational choice. It correctly distinguishes the former models as having weak induction features and the latter as being strong on this aspect.
Serich, Scott, "A Framework for Evaluating Inductive Models of Software Development" (2001). ICEB 2001 Proceedings (Hong Kong, SAR China). 163.