The Dynamics of Competitive Signalling

This dissertation investigates the use of pre-announcements (signals) as a strategic resource, focusing on how bluffing, evidence and temporal framing influence rivalry and firm performance. While signals can offer a pre-emptive advantage, they introduce uncertainty, and the mechanisms governing their impact remain empirically underexplored. To address this, a three-stage research design was employed, based around an agent-based model. This included an initial large-scale longitudinal study of the US computer hardware industry (2011-2019), which empirically validated the core phenomena, linking signal characteristics to subsequent competitive aggression. Furthermore, to understand how to best develop the simulation, an algorithmic literature analysis was also conducted to establish a cross-disciplinary multi-methodological set of practices focused on ‘simulation quality’. Finally, an empirically-grounded agent-based model was developed to explore the non-linear dynamics and performance outcomes of signalling strategies. Key findings indicate that bluffing consistently harms performance by provoking rival aggression, with penalties mitigated only partially by a firm’s reputation for truthfulness. Conversely, overtly signalling commitment through specific evidence or timelines often proved detrimental by cueing competitors. The most effective strategy to emerge was one of strategic ambiguity; not disclosing a timeline was consistently associated with enhanced performance, as it reduced rival responses without damaging reputation. The combined research supporting this thesis contributes a holistic, empirically-grounded framework for competitive market signalling, distinguishing between the strategic value of reputation and the context-dependent risks of signalling commitment.