Strategic Transparency or Deliberate Ambiguity? A Multimodal Analysis of Airline CSR Communication on LinkedIn

Airline companies face intense scrutiny concerning their societal and environmental impacts. As such, they increasingly rely on social media for Corporate Social Responsibility (CSR) communication. However, the inherently multimodal nature of these platforms complicates objective assessments of transparency. This paper introduces and empirically tests an integrated analytical framework for classifying multimodal CSR signals (soft, semi-hard, hard), enabling a systematic examination of how transparency is strategically constructed online. Drawing on a purpose-built corpus of LinkedIn posts from four major international airlines (Delta Air Lines, British Airways, ITA Airways, and China Southern Airlines), representing distinct US, Italian (EU), and Chinese communicative contexts, the analysis combines Signalling Theory, Systemic Functional Linguistics (SFL), and Multimodal Discourse Analysis (MDA). Unlike previous approaches, this framework integrates process-driven linguistic annotation and multimodal coding, enabling robust, replicable comparison across institutional contexts as well as detection of soft or obscure transparency. The findings reveal that while all companies provide clear self-presentation and some aspects of transparency, most favour soft and semi-hard signals that limit verifiable, externally validated information, with hard signalling remaining rare. In other words, selective and partial disclosure are thus strategically preferred over full transparency—underscoring how CSR communication, in practice, serves primarily to enhance corporate image rather than maximise accountability. By bridging discourse analysis with transparency metrics, the study demonstrates how digital CSR signals are classified and how strategic ambiguity and selective disclosure affect stakeholder perceptions and the credibility of corporate discourse in digital environments.