In the broad sense, the Bayesian networks (BN) are probabilistic graphical models that
possess unique methodical features to model dependencies in complex networks, such as …

The purpose of this paper is to provide a decision support system for managers to predict an
organization's probability of successful blockchain adoption using a machine learning …

The current literature claims the direct effects of industry 4.0 technologies (I4 T) on lean
manufacturing practices (LMP) and sustainable organisational performance (SOP). LMP are …

The second edition of this bestseller provides a practical and accessible introduction to the
main concepts, foundation, and applications of Bayesian networks. This edition contains a …

Introduction Unsafe behavior increases the risk of accident at workplaces and needs to be
managed properly. The aim of the present study was to provide a model for managing and …

This study explores the interplay linking Lean Six Sigma (LSS), the Circular Economy (CE)
and Industry 4.0 technologies (I4. 0T), and their impact alone or combined, on sustainable …

As mobile game business becomes one of the most lucrative as well as fast-growing
businesses, examining key success factors in this industry is of great interest. Utilizing a …

Understanding, explaining, and predicting technology acceptance have dominated the
research of information systems (IS) for more than two decades. Past research has favored …

We propose a routine for combining partial least squares-structural equation modeling (PLS-
SEM) with selected machine learning (ML) algorithms to exploit the two method's causal …

Purpose The purpose of this paper is to examine the relationship between organizational
ambidexterity, the ability of companies to explore new and to exploit existing processes …