Task complexity and informing science: A synthesis

Abstract

Task complexity is a construct widely used in the behavioral sciences to explore and predict the relationship between task characteristics and information processing. Because the creation and use of IT in the performance of tasks is a central area of informing science (IS) research, it follows that better understanding of task complexity should be of great potential benefit to IS researchers and practitioners. Unfortunately, applying task complexity to IS is difficult because no complete, consistent definition exists. Furthermore, the most commonly adopted definition, objective task complexity, tends to be of limited use in situations where discretion or learning is present, or where information technology (IT) is available to assist the task performer. These limitations prove to be severe in many common IS situations. The paper presents a literature review identifying thirteen distinct definitions of task complexity, then synthesizes these into a new five-class framework, referred to as the Comprehensive Task Complexity Classes (CTCC). It then shows the potential relevance of the CTCC to IS, focusing on different ways it could be applied throughout a hypothetical information systems lifecycle. In the course of doing so, the paper also illustrates how the interaction between different classes of task complexity can serve as a rich source of questions for future investigations.