From headlines to IPO: How AI-related media coverage of companies and leadership influences IPO durations

Abstract

Complex media environments often intertwine multiple focal actors in media reports and different characteristics of media coverage. Credibility differences among various media sub-markets further exacerbate this complexity. Previous studies have limited understanding of the interactions between different focal subjects or media characteristics. This study focuses on the niche media market of official media coverage on corporate artificial intelligence (AI)-related activities to explore the impact of official media evaluations on the duration of corporate initial public offering (IPO) processes and the nonlinear moderating role of leadership media exposure on this impact. We examined the IPO review activities of 735 Chinese firms under the under the registration-based IPO system from 2019 to 2022, with a specific focus on media sentiment analysis through supervised machine learning techniques. Our findings are largely support our hypotheses: positive evaluations by official media of corporate AI activities are associated with shorter IPO process durations, with moderate leadership media exposure being most effective in expediting the process. Additionally, although official media can filter out firms with strong AI capabilities, these firms tend to exhibit poorer profitability after their IPOs. This study establishes connections between the relatively fragmented literature on different focal subjects and media characteristics.