Exploring visual communication in corporate sustainability reporting: Using image recognition with deep learning

Author:

Nakao Yuriko1ORCID,Ishino Aya2,Kokubu Katsuhiko3,Okada Hitoshi4

Affiliation:

1. Faculty of Informatics Kansai University Takatsuki Osaka Japan

2. Faculty of Media Business Hiroshima University of Economics Hiroshima Hiroshima Japan

3. Graduate School of Business Administration Kobe University Kobe Hyogo Japan

4. Faculty of Business Administration Hiroshima University of Economics Hiroshima Hiroshima Japan

Abstract

AbstractPhotographs and images in sustainability reports can affect readers' impressions of a company. This study conducts an exploratory analysis to investigate the impact of visual content on sustainability reporting and identify corporate reporting strategies. Using image recognition with deep learning technology, we analyse how 1025 global companies, publishing reports in English, incorporate images into their sustainability reports. The study also identifies factors influencing image selection and utilisation, assessing the images based on these factors' impact. Our findings highlight that economic development, cultural preferences and industry type contribute to variations in image usage. Moreover, these influences differ according to disclosure medium (i.e., integrated or sustainability reports), revealing industry‐specific image trends and providing insights into workforce characteristics. Leveraging deep learning, the study delves into facial expressions and demographic differences in the images, providing a comprehensive understanding of corporate communication strategies.

Funder

Japan Society for the Promotion of Science

Publisher

Wiley

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