Artificial neural networks in business: Two decades of research

M Tkáč, R Verner - Applied Soft Computing, 2016 - Elsevier
In recent two decades, artificial neural networks have been extensively used in many
business applications. Despite the growing number of research papers, only few studies …

[HTML][HTML] Artificial intelligence (AI) competencies for organizational performance: A B2B marketing capabilities perspective

P Mikalef, N Islam, V Parida, H Singh… - Journal of Business …, 2023 - Elsevier
Abstract The deployment of Artificial Intelligence (AI) has been accelerating in several fields
over the past few years, with much focus placed on its potential in Business-to-Business …

Reinforcement learning and physics

JD Martín-Guerrero, L Lamata - Applied Sciences, 2021 - mdpi.com
Machine learning techniques provide a remarkable tool for advancing scientific research,
and this area has significantly grown in the past few years. In particular, reinforcement …

Concurrent reinforcement learning from customer interactions

D Silver, L Newnham, D Barker… - … on machine learning, 2013 - proceedings.mlr.press
In this paper, we explore applications in which a company interacts concurrently with many
customers. The company has an objective function, such as maximising revenue, customer …

Visualising the knowledge domain of artificial intelligence in marketing: A bibliometric analysis

E Ismagiloiva, Y Dwivedi, N Rana - … on Transfer and Diffusion of IT, TDIT …, 2020 - Springer
As the number of research outputs in the field of AI in Marketing increased greatly in the past
20 years, a systematic review of the literature and its developmental process is essential to …

Deep reinforcement learning for sequential targeting

W Wang, B Li, X Luo, X Wang - Management Science, 2023 - pubsonline.informs.org
Deep reinforcement learning (DRL) has opened up many unprecedented opportunities in
revolutionizing the digital marketing field. In this study, we designed a DRL-based …

A priori-knowledge/actor-critic reinforcement learning architecture for computing the mean–variance customer portfolio: the case of bank marketing campaigns

EM Sánchez, JB Clempner, AS Poznyak - Engineering Applications of …, 2015 - Elsevier
In this paper we propose a novel recurrent reinforcement learning approach for controllable
Markov chains that adjusts its policies according to a preprocessing and an actor-critic …

Optimal feature selection and hybrid deep learning for direct marketing campaigns in banking applications

NS Reddy - Evolutionary Intelligence, 2022 - Springer
As stated by a mass marketing technique, the objective of market-based companies is to
maximize the product of targeted direct marketing campaigns, other than reaching prospects …

[PDF][PDF] A Method of Deep Reinforcement Learning for Simulation of Autonomous Vehicle Control.

AT Huynh, BT Nguyen, HT Nguyen, S Vu, HD Nguyen - ENASE, 2021 - scitepress.org
1Faculty of Software Engineering, University of Information Technology, Ho Chi Minh City,
Vietnam 2Faculty of Information Systems, University of Information Technology, Ho Chi Minh …

Artificial Intelligence in strategic marketing: Value generation and mechanisms of action

H Singh - 2022 - ntnuopen.ntnu.no
Use of Artificial Intelligence (AI) has skyrocketed in multiple fields, and the need to deploy AI
has never been higher before. One such field to deploy AI in is marketing as it is expected to …