Integrating multi-stage data envelopment analysis and a fuzzy analytical hierarchical process to evaluate the efficiency of major global liner shipping companies

In this study, we establish a multi-stage data envelopment analysis model to evaluate the efficiency of global liner shipping companies (LSCs). Because conventional solution procedures cannot guarantee the uniqueness of solutions, in this study, we specifically devise a new two-phase algorithm to overcome this problem. The first phase ranks the priority of all stages by applying fuzzy analytical hierarchical process. The second phase then solves the efficiency score for each stage according to its priority. We established and empirically tested a three-stage research model based on data collected from the Containerization International Year Book, the Alphaliner website and annual LSC reports for the year 2012. The results show that the proposed algorithm not only determines unique solutions for the efficiency scores but also determines the priority order of the stages involved in this process. Taking advantage of the proposed model and algorithm, LSCs can effectively locate bottlenecks in their production processes and further improve them by adjusting the values of the corresponding input and output variables. In addition, the priority order of the stages obtained from the empirical study can also help LSCs allocate their resources.