Abstract:
A data envelopment analysis (DEA) is presented to assess evolutions of firm efficiency and financial performance in automotive supply chains. A sample of 32 decision-making units (DMUs), 17 globally operating original equipment manufacturers (OEMs) and 15 key suppliers from the automotive industry, is in focus of this analysis in which cost levels and capital requirements are put into relation to sales growth and profit. Cost of goods sold, operating capital, and net fixed assets represent the financial input of a company while sales growth and earnings before interest and taxes (EBIT) reflect the financial output. The financial performance of a firm is indicated by its efficiency, calculated by an input-oriented variable returns to scale model. A multiple linear regression analysis reveals which operational performance factors are predictors of financial performance. A longitudinal DEA approach that covers the years from 2003 to 2017 is chosen to reveal performance evolutions over time. In order to analyze the stability of relationships between efficient firms (peers) and inefficient ones (followers) over time, changes in the performance relationship network are assessed in a graph-theoretic approach. In this study, geographical and structural specifics of DMU groups are taken into account. The study reveals similarities and differences between OEMs and their suppliers regarding the importance of value drivers and detects periods of performance losses and recovery from the global economic crisis.