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

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  • Yuriko Nakao
  • Aya Ishino
  • Katsuhiko Kokubu
  • Hitoshi Okada

Abstract

Photographs 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.

Suggested Citation

  • Yuriko Nakao & Aya Ishino & Katsuhiko Kokubu & Hitoshi Okada, 2024. "Exploring visual communication in corporate sustainability reporting: Using image recognition with deep learning," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 31(4), pages 3210-3234, July.
    • Handle: RePEc:wly:corsem:v:31:y:2024:i:4:p:3210-3234
    DOI: 10.1002/csr.2735
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