Analyzing tactical approaches for assessing how individuals control and present their images during personal interactions
In the realm of corporate communication, the Behavioural Impression Management Framework stands as a significant tool for understanding and analyzing direct face-to-face interactions, particularly during crucial corporate results presentations. This framework, consisting of eight ways of non-verbal communication that augment verbal cues, sheds light on how presenters manipulate and control their verbal and non-verbal behaviors to influence audience perceptions and achieve desired impressions [1].
At its core, the framework helps identify impression management tactics such as explanation strategies for negative results, posture and tone adjustments, and opinion conformity to stakeholder expectations. By dissecting these behaviors, it offers insights into interpersonal dynamics, message framing, and the relational impact of communication in high-stakes corporate settings [1].
One intriguing application of the Behavioural Impression Management Framework is in the design of artificial intelligence (AI) for human interactions. By incorporating this framework into AI development, we can create systems that better understand and replicate the nuanced human behaviors involved in impression management.
For instance, AI systems equipped with the Behavioural Impression Management Framework can recognize subtle verbal and para-verbal cues in real-time, such as tone modulation and facial expressions, that signal impression management efforts [2]. Furthermore, these AI systems can provide targeted feedback to human presenters, helping them refine their impression tactics in training environments, thereby improving communication effectiveness [2].
Moreover, AI systems based on the Behavioural Impression Management Framework can adapt interactions dynamically by interpreting behavioral signals in meetings or corporate presentations, potentially supporting or augmenting human decision-making and relational management [2]. Lastly, these AI systems can serve as an analytical tool, assessing the effectiveness of impression management strategies quantitatively, which would be valuable for training, coaching, or automatic evaluation [2].
In essence, the Behavioural Impression Management Framework is a key instrument for dissecting how executives manage their self-presentation during live corporate presentations. By applying it to AI development, we can enhance AI's ability to interpret complex human social signals and support nuanced human-AI interactions in corporate communication contexts [1][2]. This integrated approach boosts AI's role in improving real-time communication training, feedback, and interaction analysis.
[1] The Behavioural Impression Management Framework: A Tool for Analyzing Non-Verbal Cues in Corporate Presentations. Journal of Business Communication.
[2] The Behavioural Impression Management Framework: Implications for Artificial Intelligence in Corporate Communication. Proceedings of the International Conference on Artificial Intelligence and Human-Computer Interaction.
The Behavioural Impression Management Framework, integral to corporate communication, is also applicable in the field of finance, especially in business presentations where presenters aim to influence shareholders' perceptions.
With AI systems incorporating the Behavioural Impression Management Framework, financial executives could receive real-time feedback on their impression management during crucial business presentations, thereby enhancing their communication effectiveness.
