Abstract Explainable Artificial Intelligence (XAI) has experienced a significant growth over
the last few years. This is due to the widespread application of machine learning, particularly …

Explainable Artificial Intelligence (XAI) has experienced a significant growth over the last few
years. This is due to the widespread application of machine learning, particularly deep …

With the rise of machine learning (ML), humans are no longer the only ones capable of
learning and contributing to an organization's stock of knowledge. We study how …

Purpose Although the value of artificial intelligence (AI) has been acknowledged by
companies, the literature shows challenges concerning AI-enabled business-to-business …

Strategic organizational decision making in today's complex world is a dynamic process
characterized by uncertainty. Therefore, diverse groups of responsible employees deal with …

Current research into algorithmic explanation methods for predictive models can be divided
into two main approaches: gradient-based approaches limited to neural networks and more …

The use of end-to-end data mining methodologies such as CRISP-DM, KDD process, and
SEMMA has grown substantially over the past decade. However, little is known as to how …

This paper links negative emotions to AI and examines their influence on aversion to
collaborating with AI in customer relationship management. It aims to understand working …

Argyris & Schön's notion of two types of learning, single‐loop (SLL) and double‐loop
learning (DLL), is arguably one of the most popularized categorizations of organizational …

Organizational learning (OL) is associated with experience and knowledge in an
organization. Information Technology (IT) enables the creation, dissemination, and use of …