Benchmark incentives and REM strategy bundling: A mixed-methods study across QUAD nations

This study employs a mixed-method approach to examine how firms combine multiple real earnings management (REM) strategies under the performance pressure of meeting earnings benchmarks. Using expert-based modeling and panel data from QUAD countries (the United States, Japan, Australia, and India) between 2003 and 2022, we assess whether REM decisions follow structured, sequenced patterns. Qualitatively, we apply Fuzzy Interpretive Structural Modeling (F-ISM) and MICMAC analysis to map interdependencies among seven EM tools. The resulting framework reveals three dominant paths, shaped by implementation cost, detection risk, and urgency to meet earnings thresholds. Empirically, we estimate REM activities using established REM models (Roychowdhury, 2006; Gunny, 2010; Srivastava, 2019), confirming the prevalence of REM in the post-SOX era. We introduce a novel REM Bundling Index to capture whether firms deploy multiple REM techniques in a given year. Regression results show that firms narrowly meeting benchmarks are significantly more likely to engage in bundling behavior. This study contributes to corporate finance theory by framing REM as a structured, constraint-driven response rather than an isolated act. By linking process modeling with empirical data, we provide a forward-looking diagnostic tool for analysts and regulators monitoring sophisticated forms of financial reporting management.