Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/118472
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Title: Discursive construction of ethical business leadership in China : a corpus-assisted ecological discourse study of online public mourning discourse
Authors: Liu, M 
Li, H 
He, W
Issue Date: Jul-2026
Source: Language sciences, July 2026, v. 116, 101828
Abstract: Inspired by Arran Stibbe’s (2024) proposal for an ecolinguistic approach to ethical leadership, this study aims to conduct a corpus-assisted ecological discourse study of online public mourning discourse following the passing of Zong Qinghou, founder of the Wahaha Group in China. An integrated analytic framework for ethical business leadership is established by drawing insights from related disciplines, such as critical discourse studies, eco-critical discourse analysis, and ecological discourse analysis. A specialized corpus was built by collecting public mourning posts on Weibo related to Zong Qinghou’s passing. Through incorporating text mining into ecological discourse analysis, this study explores the discursive constructions of an ethical business leader at multiple levels of discourse and the ecosophy behind these constructions. The findings reveal the understanding and construction of ethical business leadership in the Chinese context, and demonstrate the benefits of a corpus-assisted ecological discourse study.
Keywords: Corpus-assisted discourse study
Ecological discourse study
Leadership
Mourning
Zong Qinghou
Publisher: Elsevier Ltd
Journal: Language sciences 
ISSN: 0388-0001
EISSN: 1873-5746
DOI: 10.1016/j.langsci.2026.101828
Rights: © 2026 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
The following publication Liu, M., Li, H., & He, W. (2026). Discursive construction of ethical business leadership in China: A corpus-assisted ecological discourse study of online public mourning discourse. Language Sciences, 116, 101828 is available at https://doi.org/10.1016/j.langsci.2026.101828.
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