... squares structural equation modeling (PLS-SEM) with three machine-learning methods and is applied to survey data from 301 AI-literate professionals. Findings Fairness and accuracy are most strongly associated with GenAI usage, whereas accountability, autonomy and transparency show weaker or non...

... 2026 28 04 2026 28 04 2026 © Emerald Publishing Limited 2026 Emerald Publishing Limited Licensed re-use rights only Data science Business problems Systematic literature review Artificial intelligence Machine learning Business analytics Funding...

... in the context of explainable AI/ML. It also offers researchers a transparent, theoretically grounded framework for modelling decision-making behavior in other high-stakes contexts. The integration of artificial intelligence (AI) and machine learning (ML) into auditing has created new opportunities...

... stacked vertically: “Ontologies (Semantic Modeling)”, “NLP slash LLMs (Extraction, Conversational Interfaces)”, and “Machine Learning (Pattern Discovery)”. These blocks connect with blue arrows back to the KM processes. A blue arrow labeled “Semantic Links” from the “Ontologies (Semantic Modeling)” block...

.... Design/methodology/approach The methodology involves analyzing the proximity of rental stations to significant locations, historical demand, environmental factors and regional dynamics to inform the development of AI models. Various machine learning (ML) models were evaluated to identify an optimized...

... 13 11 2023 20 02 2024 24 05 2024 15 01 2025 11 02 2025 14 02 2025 © Emerald Publishing Limited 2025 Emerald Publishing Limited Licensed re-use rights only AHP Artificial intelligence Big data analytics DEMATEL FMCG Machine learning Organization...

...Oscar F. Bustinza; Luis M. Molina Fernandez; Marlene Mendoza Macías Purpose Machine learning (ML) analytical tools are increasingly being considered as an alternative quantitative methodology in management research. This paper proposes a new approach for uncovering the antecedents behind product...

... consisting of machine learning and bibliometric analysis. Scopus and Web of Science (WoS) are the primary databases for this purpose. Findings SCs implement cutting-edge technologies to enhance mobility, elevating information and communication technology (ICT) skills and data awareness while improving...

... from different types of manufacturing operations. The present study, therefore, aims to conduct a systematic and bibliometric-based review in the applications of machine learning (ML) techniques for sustainable manufacturing (SM). Design/methodology/approach In the present study, the authors use...

... After comparing two machine learning algorithms, we found out that self-organizing map better classifies the customer base of the retailer. The algorithm was able to extract three clusters that were described as personas using the values of the customer lifetime value and the scores of the variant...

... modeling to personnel decision-making using the design science paradigm and guided by CAM as the kernel theory. The study employed machine learning techniques, producing a model that predicts the probability of free agents signing a new contract. Also, a web-based tool was developed to help decision-makers...

... personnel. Various traditional machine learning approaches are utilised in colourimetric detection (Table 2). However, no DL-based approach, such as CNN, has been suggested for performing any colourimetric test. Table 1 Application of colourimetric tests across disciplines Field...

... a neural network method based on ensemble machine learning and dropout methods to generate several neural networks for preventing the problem of overfitting. Four machine learning techniques are applied and compared for prediction performance. Findings This study shows that the success of crowdfunding...

... decreases their attractiveness and induces loss of value. This paper introduces a new framework that aims at tackling the cultural data enrichment challenge using machine learning. Design/methodology/approach This framework focuses on the automatic annotation and metadata completion through new deep...

...Murat Özemre; Ozgur Kabadurmus Purpose The purpose of this paper is to present a novel framework for strategic decision making using Big Data Analytics (BDA) methodology. Design/methodology/approach In this study, two different machine learning algorithms, Random Forest (RF) and Artificial...