We provide the first comprehensive evidence of Apple's App Tracking Transparency policy's impact on e-commerce firms, finding substantial revenue declines particularly among smaller firms highly dependent on Meta advertising.

We analyze how intermediary online firms sustain trade despite sanctions and stigma, examining their market role and resilience strategies.

We develop neural product embeddings to predict sales of new products, addressing the challenge of forecasting with limited historical data.

We present the first evidence that organic LLM traffic delivers superior e-commerce performance compared to traditional traffic sources.

We analyze the impact of EU energy efficiency relabeling on consumer purchase decisions using quasi-experimental methods.

We analyze conversion rates in e-commerce, examining factors that influence customer purchase decisions in online retail.

We analyze how ChatGPT is disrupting traditional search behavior and its implications for Google's market dominance.

We develop interpretable deep learning models for forecasting online advertising costs, providing insights into competitive bidding dynamics.

We develop interpretable deep learning models for online advertising revenue forecasting, balancing predictive accuracy with model transparency.

We analyze how Ukrainian firms have adapted to operating during wartime, examining business resilience and survival strategies.