Valuing and Risk Analysis for Supply Chain Management

Abstract

This research presents the contribution of profitability and asset utilization to a firm's value generation from a financial market viewpoint via slack-based measure network data envelopment analysis (SBM-NDEA). Despite its superiority in performance measurement, SBM-NDEA has a limitation when confronted with new added datasets as it lacks predictive ability. To overcome this, the authors integrate twin support vector machine into it. A manager's attitude toward risks also plays an essential role in efficiency improvement and value generation, but numerical messages do not convey such information. Textual messages with elastic natures thus bring information beyond just numerical messages. To assist users in quantifying risk types, the authors introduced an advanced text analyzer to conjecture a manager's attitude toward each risk. The results show that the performance evaluation model with forecasting capability can shift the manager's role from monitoring the past to planning the future. This study also demonstrates that the model with textual information reaches superior forecasting performance.