Hybrid Kernelized Fuzzy Clustering and Multiple Attributes Decision Analysis for Corporate Risk Management

Abstract

This study introduces an emerging risk management architecture by extending balanced scorecards (BSC) with risk exposure considerations for corporate operating performance assessment and then constructs a hybrid mechanism that combines kernelized fuzzy C-means (KFCM), multiple attributes decision analysis (MADA), and extreme learning machine (ELM) for corporate operating performance forecasting. KFCM is implemented to do the clustering task for each corporate under each aspect of BSC. No specific corporate reaches optimal performance under each assessing measure-that is, dissimilar assessing criteria leads to dissimilar outcomes. This method can be transformed into a MADA task and a MADA algorithm that can yield a reliable outcome systematically. Sequentially, the outcome is fed into ELM to construct the performance forecasting mechanism. The introduced mechanism with outstanding forecasting performance comes with a critical challenge: it lacks interpretability, which impedes its real-life usage. To cope with this problem, the rough set theory (RST) is employed to extract the inherent decision logics from the black-box model and visualize it in human readable formats. The introduced model has been examined by real cases and is a promising alternative for corporate risk management.

Enterprise Performance Optimization Management Decision-Making and Coordination Mechanism Based on Multiobjective Optimization

“…It is a comprehensive application of psychology, sociology, social psychology, anthropology, economics, political science, history, law, education, psychiatry, marketing, and management theories and methods to study human behavior borderline subjects. Behavioral science was once called interpersonal relations [6].…”

“…(1) Pay attention to the integrity of the system: first of all, the people, things, and environment in the enterprise are regarded as a complete system, which in turn lives in a larger system. en, use system thinking and system analysis method to view the problem from the overall framework, recognize the problem, analyze the problem, and finally solve and deal with the problem [6].…”

News-Based Soft Information as a Corporate Competitive Advantage

“…To examine the effectiveness of FS, we consider two scenarios: (1) with FS and (2) without FS. To access a more robust outcome, we take the introduced model as a benchmark and compare it with four other models for predicting financial troubles, such as Bayesian belief network (BBN) (Kirkos, Spathis, & Manolopoulos, 2007), Adaptive neuro fuzzy inference system (ANFIS) (Pan, 2009), Support vector machine (SVM) (Shie, Chen, & Liu, 2012), and extreme learning machine (ELM) (Lin, 2017). To avoid the result just happening by chance, we perform a statistical examination.…”