Increasing Shareholder Value Through Supply Chain Management – Results of a European Wide Empirical Investigation in Logistics

The statement that supply chain management (SCM), defined as; “the integration of business processes from end user through original suppliers that provide products, services and information that add value for customers” (Cooper, Lambert, Pagh 1997, p.1-14) contributes to making companies more customer-oriented, competitive and effective is nowadays widely accepted (Li, 2006, p.107-124). Management also agrees that a direct connection between supply chain performance and financial results (market capitalization) exists. In fact, virtually all wining business strategies have supply chain strategies as their core strategies (D’Avanzo, 2003, p. 40-47) Up to date supply chain management does not show the correlations between actions taken and the overall supply chain performance, competitiveness and increase in shareholder value (Lambert, 2001, p. 1-19). In order to eliminate this problem supply chain management should be linked to Shareholder Value. The value-driven SCM approach in this paper uses EVA™. EVA is defined as the residual wealth calculated by subtracting the cost of capital from operating profit after taxes. If residual wealth is positive, the operational business can cover total costs including the cost of all capital employed. (equity and liabilities). If EVA is negative, value is being destroyed and the company faces the flight of capital and a lower stock price (Stewart, G.B. 1991). In order to create value EVA and SCM must linked. Financial value affecting EVA has been determined by the authors as Profitability, Revenue Growth, Cash-to-cash cycle and Fixed Assets Turnover. DESIGN/METHODOLOGY/APPROACH The linkage between supply chain management, the value drivers and shareholder value will be enforced by presenting an empirical study done in the Amadeus Top 250.000 database. In this study approximately 7.500 companies in Europe during a ten year period where chosen to participate. Selection variables included SIC code, revenue, cost of goods sold, inventory, payables, and receivables. Companies with incomplete data for the selected variables in the period were removed from the dataset. This resulted in a usable set of 6,925 companies.