A flow-to-equity approach to coordinate supply chain network planning and financial planning with annual cash outflows to an institutional investor

Business Research

Wolfgang Albrecht¹  Martin Steinrücke¹ 

[1]Faculty of Law and Economics, University of Greifswald

关键词: Company takeover;    Flow-to-equity method;    Annual cash outflows to the investor;    Supply chain design;    Capacity profiles;    Mixed-integer non-linear programming;   

DOI  :  10.1007/s40685-016-0037-4

来源: DOAJ

【 摘 要 】

Abstract A common side effect of cross-linked global economies is that well-positioned middle class companies are acquired by institutional investors, which formulate unreasonable return expectations in many cases. As a consequence, the resulting payouts are often not in line with business operations so that even world market leaders get into trouble or close down. In this context, we consider the case of a sanitary company, which had to manage the described situation after a business takeover. In order to coordinate the annual cash outflows to the investor with intra-organizational supply chain planning and financial planning, we propose a mixed-integer non-linear programming model that is based on the flow-to-equity discounted cash flow method. The objective is to maximize the present value of equity while determining annual cash outflows to the institutional investor during his engagement. As the decisions of the investor during his engagement influence possible operations of the company after his engagement, the residual value of equity (that influences the selling price) is taken into account. The modeling is based on cash flow series, which result from supply chain operations and restructuring on the one hand, and from financial transactions on the other. Financing is characterized by interest rates depending on the time period the credit starts, the credit period, the debt limit of the company and the current total debt. As the latter is a result of the optimization, non-linearity arises. Nevertheless, both the expected demand scenario and further randomly generated demand scenarios of the sanitary company could be solved to the optimum with the commercial optimization package GAMS 23.8/SCIP 2.1.1 within acceptable computation times, if capacity profiles are assigned to the locations to depict feasible and/or preferred capacity developments.

【 授权许可】

Unknown