Despite the prevalence of photographs in corporate sustainability reporting, their use is not yet sufficiently understood. To the best of our knowledge, this paper is the first large‐scale study in the field. Introducing a novel machine‐supported approach, we assess environmental photograph...

This article surveys the economic literature on the role of mass media and social media for the dissemination of news about gross domestic product (GDP), inflation, unemployment and the economy at large. Focusing on studies that use media content data, two key insights emerge. First, identical...

We construct a neural network algorithm that generates price predictions for art at auction, relying on both visual and non-visual object characteristics. We find that higher automated valuations relative to auction house pre-sale estimates are associated with substantially higher...

We propose a demand estimation method that allows researchers to estimate substitution patterns from unstructured image and text data. We first employ a series of machine learning models to measure product similarity from products' images and textual descriptions. We then estimate a nested logit...

Purpose In this study the authors aim to outline new ways of information extraction for automated valuation models, which in turn would help to increase transparency in valuation procedures and thus contribute to more reliable statements about the value of real estate....

We propose a demand estimation method that allows researchers to estimate substitution patterns from unstructured image and text data. We first employ a series of machine learning models to measure product similarity from products' images and textual descriptions. We then estimate a nested logit...