Accountants' usage of causal business models in the presence of benchmark data:: A note

• 成果类型: Article
• 署名作者: Vera-Munoz, Sandra C.; Shackell, Margaret; Buehnr, Marc
• 署名单位: University of Notre Dame; Cardiff University
• 刊物名称: CONTEMPORARY ACCOUNTING RESEARCH
• ISSN/ISSBN: 0823-9150
• DOI: 10.1506/car.24.3.12
• 发表日期: 2007
• 页码: 1015-+
• 关键词: temporal contiguity; COMPETITOR ANALYSIS; covariation; performance; JUDGMENT; experience; KNOWLEDGE; INFORMATION; feedback; utility

摘要

Performance measurement systems often incorporate cause-and-effect theories in business models, while the literature questions accountants' and managers' ability to use and understand the very business models that they value. We address this question: Does articulation of a business model as a cause-and-effect theory enhance an accountant's evaluation of benchmark data that requires implicit cause-and-effect covariation assessments? We prompt (or do not prompt) accountants with a causal business model and with benchmark data that either support or do not support the model and ask the accountants to make budget allocation recommendations. We find that accountants prompted with causal-model information are more able to interpret and exploit cause-and-effect covariation information that is implied in the benchmark data. Furthermore, we find that providing causal-model information offers the potential for a beneficial effect - but no detrimental effect - in guiding covariation judgements, even when the benchmark data do not support the model. Taken together, our results suggest that in the presence of benchmark data, causal-model information compensates for the lack of causal knowledge by guiding accountants' covariation assessments. We discuss implications for research and practice and provide directions for future research.