Strategic Vagueness and Multimodal Meaning-Making in Senior Executive Communication: How Nonverbal Cues Interact with Vague Language to Shape Meaning
Abstrak
Vague language (VL) is often seen as imprecision; however, in executive communication, it can function as a strategic resource. This study examines how senior executives combine VL with nonverbal cues in unscripted interviews, drawing on 10 recordings with C-suit leaders, primarily CEOs, from Stanford’s View from the Top Series. Unlike previous research focusing on written or monomodal data, the study introduces an integrative analytical framework that examines the interplay between linguistic vagueness and nonverbal cues to capture the strategies leaders use to communicate effectively while employing vague expressions. To this end, multimodal features, including speech, hand gestures, gaze, head movements, and prosody, are annotated and analyzed using a sequence of quantitative techniques. Multivariate Analysis of Variance (MANOVA) was applied to test whether different types of VL significantly influenced the use of multimodal features, followed by Multiple Correspondence Analysis (MCA), hierarchical cluster analysis, and Latent Class Analysis (LCA) to identify recurrent multimodal configurations associated with VL use. Results show that in these high-stakes business interactions, VL is enacted not merely as a linguistic phenomenon: nonverbal cues are integral to conveying meaning. These modes interact with speech to modulate claims, stance, and social alignment, collectively supporting pragmatic functions such as politeness, persuasion, and self-protection. VL thus operates as part of systematic multimodal ensembles, functioning as a strategic communicative resource rather than a sign of weakness. The study advances our understanding of leadership discourse and offers practical implications for executive communication training, highlighting the importance of developing multimodal awareness in high-stakes professional contexts.
Penulis (1)
Omra Malladi
Akses Cepat
- Tahun Terbit
- 2026
- Bahasa
- en
- Sumber Database
- Semantic Scholar
- DOI
- 10.1177/23294884261421508
- Akses
- Open Access ✓