Earnings Management Behavior of Enterprise Managers Based on Evolutionary Game Theory

Wang, Yang; Li, Anqi; Liu, Jiahuan

doi:10.1155/2022/8037226

Cited by 2 publications

(2 citation statements)

References 9 publications

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“…The core of evolutionary game theory (EGT) lies in participants adjusting strategies based on a comparison of individual versus average benefits, aiming for an evolutionary equilibrium where benefits are optimized [13]. This theory is deeply rooted in economic analysis and is particularly relevant for examining strategic interactions between governments and businesses, and within enterprises [14][15][16][17], making cost management a crucial aspect of the game.…”

Section: Cost Measurement Of Cre Using Activity-based Costing Methodsmentioning

confidence: 99%

Analyzing and Simulating Evolution of Subsidy–Operation Strategies for Multi-Type China Railway Express Operation Market

Feng,

Zhang,

Cai

et al. 2024

Mathematics

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The China Railway Express stands as a crucial facilitator of trade across the land routes of Eurasian countries. During its initial developmental phase, the China Railway Express heavily relied on subsidies to establish a market presence. This dependency hindered its independence and sustainability. Hence, there exists a paramount need to regulate the subsidy market and institute more rational operation strategies. This study focuses on the dynamics of the subsidies and operations in the market for the China Railway Express under different types of development models. It uses evolutionary game theory and the Activity-Based Costing (ABC) method to describe the dynamic evolution of four cases between local governments and operating-platform enterprises. Four corresponding lines were selected as instances: from Xiamen, Wuxi, Changsha, and Zhengzhou to Malaszewicze, Poland. The findings conclude that the optimal conditions for the development of the China Railway Express market exist when operating-platform enterprises possess higher assets and the local government’s supervision and punishment of the market are relatively weaker. This study offers valuable insights for guiding subsidy and operational decision-making processes for the China Railway Express.

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Section: Cost Measurement Of Cre Using Activity-based Costing Methodsmentioning

confidence: 99%

Analyzing and Simulating Evolution of Subsidy–Operation Strategies for Multi-Type China Railway Express Operation Market

Feng,

Zhang,

Cai

et al. 2024

Mathematics

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“…Evolutionary game theory was applied in the study [37] to analyze the motives and behaviors of managers related to earnings manipulation to detect nancial statement fraud. It was discovered that strengthening monitoring mechanisms and penalizing earnings management behavior are effective ways to quickly curtail fraudulent activity.…”

Section: Game Theory and Machine Learning In Fraud Detectionmentioning

confidence: 99%

Modeling the Dynamic Behaviors of Bank Account Fraudsters Using Combined Simultaneous Game Theory with Neural Networks

USMAN,

Abdullahi,

Ran

et al. 2024

Preprint

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New bank account fraud is a significant problem causing financial losses in banking and finance. Existing statistical and machine-learning methods were used to detect fraud thereby preventing financial losses. However, most studies do not consider the dynamic behavior of fraudsters and often produce a high False Positive Rate (FPR). This study proposes the detection of new bank account fraud in the context of simultaneous game theory (SGT) with Neural Networks, the SGT involves two players, a fraudster, and bank officials attacking each other through Bayesian probability in a zero-sum. The influence of outliers within the SGT was tackled by adding a context feature for effective simulation of the dynamic behavior of fraudsters. The Neural Networks layer uses the simulated features for fraud context learning. The study is validated using Bank Account Fraud (BAF) Dataset on different machine-learning models. The Radial Basis Function Networks achieved FPR of 0.0% and 8.3% for fraud and non-fraud classes, respectively, while achieving True Positive Rate (TPR) of 91.7% and 100.0% for fraud and non-fraud classes, respectively. An improved Radial Basis Function Networks detect fraud by revealing fraudulent patterns and dynamic behaviors in higher dimensional data. The findings will enhance fraud detection and reduce customer attrition.

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Earnings Management Behavior of Enterprise Managers Based on Evolutionary Game Theory

Cited by 2 publications

References 9 publications

Analyzing and Simulating Evolution of Subsidy–Operation Strategies for Multi-Type China Railway Express Operation Market

Analyzing and Simulating Evolution of Subsidy–Operation Strategies for Multi-Type China Railway Express Operation Market

Modeling the Dynamic Behaviors of Bank Account Fraudsters Using Combined Simultaneous Game Theory with Neural Networks

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