• Media type: E-Book
  • Title: Firms’ Rhetorical Nationalism : Theory, Measurement, and Evidence from a Computational Analysis of Chinese Public Firms
  • Contributor: Yue, Lori [VerfasserIn]; Zheng, Jiexin [VerfasserIn]; Mao, Kaixian [VerfasserIn]
  • imprint: [S.l.]: SSRN, [2023]
  • Extent: 1 Online-Ressource (63 p)
  • Language: English
  • DOI: 10.2139/ssrn.4486246
  • Identifier:
  • Keywords: rhetorical nationalism ; machine learning ; word embedding model ; Chinese public firms
  • Origination:
  • Footnote: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments June 20, 2023 erstellt
  • Description: In this paper, we develop a computational measure of rhetorical nationalism for Chinese public firms. We first review the literature and develop a four-dimensional theoretical framework of nationalism relevant to firms: national pride, anti-foreign, dominant agenda (national revival), and corporate role. We then use machine-learning-based text analysis of over 41,000 annual reports of Chinese public firms from 2000 to 2020 and identify a dictionary of words for each dimension. Using a weighted ratio of nationalism-related words, we describe the overall picture of Chinese public firms’ rhetorical nationalism and provide the first empirical evidence regarding rising rhetorical nationalism among Chinese firms. Firms’ demonstration of rhetorical nationalism is related to both strategic and socialization factors; Firms that are SOEs, older, larger, more profitable, consumer-facing, with more individual investors and less income from overseas demonstrate a higher level of nationalism. Firms that demonstrate more rhetorical nationalism also have a better future financial return. Our study provides a theoretical framework for organizational study of nationalism and a new measure for firms’ rhetorical nationalism, and demonstrates that the rising rhetorical nationalism among Chinese firms is more strongly driven by firms’ motivations to appeal to domestic investors and consumers than to obtain government subsidies
  • Access State: Open Access