Authors: Peter Wanke; Zhongfei Chen; Jorge Junio Moreira Antunes; Carlos Barros
Addresses: COPPEAD Graduate Business School, Federal University of Rio de Janeiro, Rua Paschoal Lemme, 355, 21949-900 Rio de Janeiro, Brazil ' China Research Centre for Economic Development and Innovation Strategy, School of Economics, Jinan University, Huangpu West Road No. 601, Guangzhou, Guangdong 510632, China ' COPPEAD Graduate Business School, Federal University of Rio de Janeiro, Rua Paschoal Lemme, 355, 21949-900 Rio de Janeiro, Brazil ' Instituto Superior de Economia e Gestão, University of Lisbon, Rua Miguel Lupi, 20; 1249-078, Lisbon, Portugal
Abstract: 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.
Keywords: Chinese ports; data envelopment analysis; DEA; general multi-stage system; GMSS; Malmquist index; regression trees; bootstrapping; China.
International Journal of Shipping and Transport Logistics, 2018 Vol.10 No.2, pp.202 - 236
Received: 20 Jan 2017
Accepted: 05 Apr 2017
Published online: 11 Jan 2018 *