Journal of Modelling in Management: Volume 17 Issue 3

Guest editorial: Artificial intelligence and machine learning in business and management

Fouad Ben Abdelaziz, Herb Kunze, Davide La Torre, Bernard Sinclair-Desgagné

Distributed model for customer churn prediction using convolutional neural network

Muhammad Usman Tariq, Muhammad Babar, Marc Poulin, Akmal Saeed Khattak

The purpose of the proposed model is to assist the e-business to predict the churned users using machine learning. This paper aims to monitor the customer behavior and to perform…

Optimization algorithms and investment portfolio analytics with machine learning techniques under time-varying liquidity constraints

Mazin A.M. Al Janabi

This paper aims to examine from commodity portfolio managers’ perspective the performance of liquidity adjusted risk modeling in assessing the market risk parameters of a large…

Data mining techniques for predicting the financial performance of Islamic banking in Indonesia

Mohammed Ayoub Ledhem

The purpose of this paper is to apply various data mining techniques for predicting the financial performance of Islamic banking in Indonesia through the main exogenous…

Applications of artificial intelligence and machine learning within supply chains:systematic review and future research directions

Hassan Younis, Balan Sundarakani, Malek Alsharairi

The purpose of this study is to investigate how artificial intelligence (AI), as well as machine learning (ML) techniques, are being applied and implemented within supply chains…

Predicting business processes of the social insurance using recurrent neural network and Markov chain

Mehrdad Fadaei PellehShahi, Sohrab Kordrostami, Amir Hossein Refahi Sheikhani, Marzieh Faridi Masouleh

Predicting the final status of an ongoing process or a subsequent activity in a process is an important aspect of process management. Semi-structured business processes cannot be…

An integrated framework for predicting the best financial performance of banks: evidence from Egypt

Mohamed El-Sayed Mousa, Mahmoud Abdelrahman Kamel

This study aims to develop and test a framework for integration between data envelopment analysis (DEA) and artificial neural networks (ANN) to predict the best financial…

Cost-sensitive meta-learning framework

Samar Ali Shilbayeh, Sunil Vadera

This paper aims to describe the use of a meta-learning framework for recommending cost-sensitive classification methods with the aim of answering an important question that arises…

Evaluation of the components of intelligence and greenness in Iranian ports based on network data envelopment analysis (DEA) approach

Esmaeil Sadri, Fatemeh Harsej, Mostafa Hajiaghaei-Keshteli, Jafar Siyahbalaii

Creating green ports, while observing international and international standards and maritime conventions and regulations and moving toward smart ports, can increase the speed of…

Linear optimal weighting estimator (LOWE) for efficient parallel hybridization of load forecasts

Fatemeh Chahkotahi, Mehdi Khashei

Improving the accuracy and reducing computational costs of predictions, especially the prediction of time series, is one of the most critical parts of the decision-making…