The effects of task complexity and skill on over/under-estimation of internal control

Purpose – Using Bonner's model, this paper aims to examine the effects of skill level and the two task complexity dimensions – clarity and quantity of information – on subjects' internal control risk assessments. Design/methodology/approach – The research expands the literature by isolating the individual components of task complexity and examining how skill interacts with either component in affecting decision making. It uses a 2×4 mixed factors laboratory experiment. This design allows the effects of task complexity and skill between and within subjects to be examined. The mixed factors design includes two levels (high and low) for each dimension of task complexity (clarity and quantity) on a between-subjects basis, with four separate cases on a within-subjects basis. Skill level is measured as the subject's task-related knowledge. The subjects are senior-level students in auditing courses at three Midwest universities. Findings – It is found that subjects assess control risk too high, consistent with the conservatism principle. Skill level mediates this finding: high-skill subjects make more accurate risk assessments; low-skill subjects consistently assess control risk too high. Over repetitions of complex tasks, high-skill subjects make more accurate assessments, while low-skill subjects initially overstate, then improve. For repetitive simple tasks, both skill levels get worse, increasingly overstating their assessments. These findings support current practice, indicating that experienced auditors make complex risk assessments, where repetitive performance of complex tasks improves risk assessments. However, repetitive simple tasks may result in assessing control risk too high, resulting in excessive testing. Originality/value – Consistent with prior research, the results suggest task complexity and subject skill are important considerations in experimental research designs.