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Chinese Journal of Management Science ›› 2018, Vol. 26 ›› Issue (2): 62-70.doi: 10.16381/j.cnki.issn1003-207x.2018.02.007

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Robust Optimization Model of Supply Chain Based on EVA and Operational Risk Breference

YU Li-ping, LIN Li-feng, QIU Ruo-zhen   

  1. School of Business Administration, Northeastern University, Shenyang 110819, China
  • Received:2016-03-09 Revised:2017-07-10 Online:2018-02-20 Published:2018-04-20

Abstract: Creating shareholder value is commonly considered as the paramount business goal, which depends on the performance model and risk management. The core concept of Economic Value Added (EVA), as a prevalent metric of value-based performance, is capital cost that is uncertain due to the interest of debt and the hurdle rate changing, and thus there is much risk of cash flow in value creation. A major factor causing operational risks is the uncertainty of product demand. In addition, due to the operating leverage, fluctuation of demand may cause more change in operating income, and influence value creation directly. Recent papers show increasing interest in value-based supply chains management. However, these researches neglect the influence of risk preference of decision-makers on EVA, and ignore the corresponding risk from the uncertainty of capital cost.
In the multi product and multi stage supply chain that compose of one manufacturer and multiple external suppliers,economic value added (EVA) is regarded as a performance index to reflect the value creation,the management risk preferences of decision makers are considred,and the discrete scenario with known probabilities is adopted to describe the fluctuation of capital costs and demand and uses robust stochastic programming method to establish a robust optimization model of supply chain based on the goal of value creation. The objective function of the model includes three items, the first item is the expected EVA; the second is the product of risk preferences parameter of decision makers with business risk measured operating leverage coefficients; the third is feasible penalty function to punish deviation control constraints. The constraints consider comprehensively the financial constraints associated with supply chain capital flow and the non-financial constraints with supply chain logistics The decision goal hopes to get optimal solution (robust solution) which is feasible (model robust) under any uncertain situation when supply chain performance and risk are optimized comprehensively.
Application analysis results show that the model can integrate the performance and risk management, and reduce the influence of uncertain capital cost and demand, obtain the optimal solution with robustness. What is more, the decision maker with high risk averse prefer to give up the larger EVA to maintain a lower business risks. Meantime, the decision makers can choose different weight coefficients to focus on robust solution or model robust, ensure the robustness of supply chain operation and achieve the goal of value creation.

Key words: EVA, risk preference, value creation, capital cost, robust optimization

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