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Constructing Innovation: How Firms Use Market Communication to Shape Perceptions of Innovation

Aston University College of Business and Social Sciences
✓ Fully Funded 🎓 Business & Management natural language processing large language models market communication innovation perception earnings call communication strategic communication financial markets marketing theory

Explore how firms craft innovation messages to shape market perceptions. Use NLP and language models to analyze earnings calls and reveal the gap between communication and actual innovation.

AI-generated overview

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Why This Research Matters

This research reveals how firms influence investor and stakeholder beliefs about innovation through communication, which can significantly impact firm valuation and competitive positioning. Understanding this dynamic supports the creation of more credible and effective narratives, reducing misinformation and enhancing market efficiency.

Communicated Innovation Realised Innovation Earnings Call Communications Natural Language Processing Market Perceptions Strategic Marketing

Project Description

Project Overview

In contemporary markets, competitive advantage depends not only on firms’ ability to innovate, but also on how innovation is communicated and perceived by external stakeholders. Prior research predominantly views innovation as an objective output but overlooks the role of communication in shaping market beliefs under uncertainty. This project reconceptualises innovation as a perception-based construct co-created through firm communication and stakeholder interpretation, focusing on earnings call communications as a strategic marketing tool through which firms construct narratives about their innovation.

What You Will Do

You will analyze large-scale textual data from earnings call transcripts combined with firm-level financial, analyst, and innovation data. Utilizing both traditional natural language processing techniques and advanced large language models, you will study how firms use language, framing, and narratives to influence stakeholder perceptions of innovation, and investigate the alignment or divergence between communicated and realised innovation.

Expected Outcomes

This research will clarify the "talk–walk gap" between firms’ communication and actual innovation outputs. It will advance marketing and innovation theory by positioning firm communication as key to constructing intangible asset value, and offer practical insights for firms to design credible innovation narratives and manage stakeholder expectations effectively.

Why This Matters

The project addresses a critical gap in understanding how intangible assets like innovation are perceived and valued in markets. By integrating communication, perception, and innovation outcomes, the research supports firms in sustaining long-term value in information-driven markets, offering both theoretical and practical advances in competitive strategy and financial communication.

Entry Requirements

Applicants should hold or expect to achieve a First or Upper Second Class Honours undergraduate degree and a Masters degree with Merit or Distinction in relevant subjects. Overseas qualifications will be considered if equivalent. Supporting documents include transcripts, research and personal statements, CV, two academic references, English language evidence, and passport copy.

How to Apply

Applications must be complete with all supporting documents including transcripts, certificates, research statement, personal statement, CV, two academic references, proof of English language proficiency, and passport copy. References may be submitted later if necessary. For enquiries, contact details are not fully provided in the text.

Eligibility

UK/Home
EU
International

Supervisor Profile

PM
Prof Marian Garcia
Aston University, College of Business and Social Sciences

Prof Marian Garcia is a scholar based at Aston University's College of Business and Social Sciences. Her research focuses on innovation strategy, market communication, and the intersection of marketing and financial disclosure. She is known for applying quantitative textual analysis methods, including NLP, to understand how firms construct strategic narratives around innovation and intangible assets.

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