Grand Narratives, Grim Realities? ESG Rhetoric and Legitimacy Management in the Taiwanese Food Industry

In the food industry, operational safety is inextricably linked to public trust, making occupational accidents a severe threat to organizational legitimacy. When safety failures occur, they are interpreted not merely as material risks but as profound moral breaches that demand a strategic response. While Western institutional logic predicts that firms will repair this trust through transparency and direct accountability, this assumption often conflicts with the indigenous values of East Asian’s face culture, which prioritizes dignity and the avoidance of public shame. To bridge this gap between theoretical expectations and indigenous practice, this study proposes a framework of “face deflection” to examine how firms navigate legitimacy threats. Using Structural Topic Modeling (STM), we analyzed the “Letter to Shareholders” in the ESG reports of listed Taiwanese food companies from 2021 to 2024 to test the relationship between rhetorical topics and the Occupational Accident Rate (OAR). The empirical results reveal a distinct cultural logic: as accident rates rise, firms do not increase disclosures related to routine compliance or affective care. Instead, they significantly mobilize grand narrative rhetoric, characterized by abstract, future-oriented themes such as AI and global governance, to actively assert Mianzi (social face) and deflect attention from the damaged Lian (moral face). These findings challenge the universality of transparency-based legitimacy repair, demonstrating that in Confucian societies, firms employ rhetorical abstraction to mask operational failures.

Publication Details

Journal
International Journal of Academic Research in Business and Social Sciences
Published
2025-12-17
DOI
https://doi.org/10.6007/ijarbss/v15-i12/27152
Primary Topic
Computational and Text Analysis Methods
Type
article
Field-Weighted Citation Impact
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article

Grand Narratives, Grim Realities? ESG Rhetoric and Legitimacy Management in the Taiwanese Food Industry

International Journal of Academic Research in Business and Social Sciences
Computational and Text Analysis Methods
article

Grand Narratives, Grim Realities? ESG Rhetoric and Legitimacy Management in the Taiwanese Food Industry

article en

Abstract

In the food industry, operational safety is inextricably linked to public trust, making occupational accidents a severe threat to organizational legitimacy. When safety failures occur, they are interpreted not merely as material risks but as profound moral breaches that demand a strategic response. While Western institutional logic predicts that firms will repair this trust through transparency and direct accountability, this assumption often conflicts with the indigenous values of East Asian’s face culture, which prioritizes dignity and the avoidance of public shame. To bridge this gap between theoretical expectations and indigenous practice, this study proposes a framework of “face deflection” to examine how firms navigate legitimacy threats. Using Structural Topic Modeling (STM), we analyzed the “Letter to Shareholders” in the ESG reports of listed Taiwanese food companies from 2021 to 2024 to test the relationship between rhetorical topics and the Occupational Accident Rate (OAR). The empirical results reveal a distinct cultural logic: as accident rates rise, firms do not increase disclosures related to routine compliance or affective care. Instead, they significantly mobilize grand narrative rhetoric, characterized by abstract, future-oriented themes such as AI and global governance, to actively assert Mianzi (social face) and deflect attention from the damaged Lian (moral face). These findings challenge the universality of transparency-based legitimacy repair, demonstrating that in Confucian societies, firms employ rhetorical abstraction to mask operational failures.

International Journal of Academic Research in Business and Social SciencesVol. 15(12)
Openalex Percentile: Top 24%
Computational and Text Analysis Methods
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