Decoding effort: Toward a measure – and a better understanding – of effort intensity in accounting research
引入瞳孔测量法直接捕捉努力强度，通过解码任务实验发现计件工资与固定工资通过瞳孔扩张部分中介影响绩效，且该效应随时间减弱，为管理控制系统的行为影响研究提供新工具。
This study introduces pupillometry – the measurement of pupil diameter changes – as a direct approach to capturing effort intensity in management accounting research. Traditional approaches using self-reports or performance-based proxies have limited researchers’ ability to study how management control systems influence behavior through effort. Using a controlled experiment with a decoding task, we examine how piece-rate versus flat-wage compensation influences effort intensity and performance. Our findings show that pupil dilation partially mediates the relationship between incentives and performance, with this mediation strongest in early experimental rounds before weakening over time. This dynamic pattern suggests that while incentives initially influence performance through effort intensity, other mechanisms such as implicit learning emerge in later rounds. Beyond demonstrating pupillometry’s validity for measuring effort intensity, we highlight its potential applications across management accounting research streams, enabling researchers to better understand how control system elements influence behavior through effort.