Malmquist productivity indexes in Chinese ports: a fuzzy GMSS DEA approach

This research focuses on the productivity assessment of 17 major Chinese ports from 2006-2015. Differently from previous works, a network productive structure formed by two stages was considered. In the first stage, fixed and other assets, altogether with human resources, are used to generate operating costs used as intermediate inputs, while the depreciation/amortisation of such assets is considered as an exogenous output. In the second stage, each port uses these costs generated in the first stage to produce operating profit, while cargo demand is considered as an exogenous input that enters the system. Then, bootstrapped regression trees are used to predict the relationship of a set of contextual variables related to the technology, financial health and location. Results indicate that the former two determine the productivity change of Chinese ports. When the expansion of scale has not jeopardised the financial health, the productivity will increase. Implications are also derived.