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 …

Artificial intelligence and algorithmic decision-making processes are increasingly criticized
for their black-box nature. Explainable AI approaches to trace human-interpretable decision …

Recommender systems provide personalized service support to users by learning their
previous behaviors and predicting their current preferences for particular products. Artificial …

With the growing presence of algorithms and their far-reaching effects, artificial intelligence
(AI) will be mainstream trends any time soon. Despite this surging popularity, little is known …

As algorithm-based services increase, social topics such as fairness, transparency, and
accountability (FAT) must be addressed. This study conceptualizes such issues and …

Algorithms are progressively transforming human experience, especially, the interaction with
businesses, governments, education, and entertainment. As a result, people are growingly …

Although algorithms have been widely used to deliver useful applications and services, it is
unclear how users actually experience and interact with algorithm-driven services. This …

The recent proliferation of artificial intelligence (AI) gives rise to questions on how users
interact with AI services and how algorithms embody the values of users. Despite the …

Recommender systems are currently successful solutions for facilitating access for online
users to the information that fits their preferences and needs in overloaded search spaces. In …

Recommender systems (RSs) are programs that apply knowledge discovery techniques to
make personalized recommendations for user's information on the web. In online sharing …