This paper synthesises research on artificial intelligence (AI) in e-commerce and proposes
guidelines on how information systems (IS) research could contribute to this research …

Explainable recommendation attempts to develop models that generate not only high-quality
recommendations but also intuitive explanations. The explanations may either be post-hoc …

Text-to-image models offer unprecedented freedom to guide creation through natural
language. Yet, it is unclear how such freedom can be exercised to generate images of …

Text-to-image personalization aims to teach a pre-trained diffusion model to reason about
novel, user provided concepts, embedding them into new scenes guided by natural …

On the Internet, where the number of choices is overwhelming, there is need to filter,
prioritize and efficiently deliver relevant information in order to alleviate the problem of …

Text-to-image (T2I) personalization allows users to guide the creative image generation
process by combining their own visual concepts in natural language prompts. Recently …

This study explores the relationship between digital marketing practices, customer
satisfaction, customer involvement, and purchase intention. The focus is on the life …

Recommender systems have become an important research field since the emergence of
the first paper on collaborative filtering in the mid-1990s. Although academic research on …

Learning analytics are rapidly being implemented in different educational settings, often
without the guidance of a research base. Vendors incorporate analytics practices, models …

Multiple criteria decision making (MCDM) is widely used in ranking one or more alternatives
from a set of available alternatives with respect to multiple criteria. Inspired by MCDM to …