Leveraging structural topic modeling to compare “Green Port” research and practice

Abstract

Although the concept of “green ports” was first introduced by practitioners in the 2000s and attracted significant attention from academia, academic investigations have not comprehensively reflected practitioners’ concerns. To narrow the gaps in the definition of the concept between academia and practitioners and to avoid unclear understandings that jeopardize the value of related research, this study investigates practitioners’ perceptions of green ports through the theoretical lens developed by academia and to identify and explain these gaps. Natural language processing, one of the most advanced text mining methods, is applied to analyze 1781 chunks of green port-related text retrieved from 123 corporate social responsibility reports released by 15 mainland Chinese listed port companies from 2010 to 2021. The results suggest the following: (1) while there is a general consensus between academia and practitioners, significant differences emerge in certain topics, such as noise pollution, land pollution, safety management, and green education. (2) The dynamic and socially constructed nature of green ports is highlighted, suggesting that the influence of the external socioeconomic environment, including site disparity, social patterns and significant local disasters, should be integrated into future research. Finally, suggestions for narrowing the gap between academia and practitioners regarding perceptions of green ports are proposed.