Machine learning in marketing: Recent progress and future research directions

D Herhausen, SF Bernritter, EWT Ngai, A Kumar… - Journal of Business …, 2024 - Elsevier
Decision-making in marketing has changed dramatically in the past decade. Companies
increasingly use algorithms to generate predictions for marketing decisions, such as which …

A methodological and theoretical framework for implementing explainable artificial intelligence (XAI) in business applications

D Tchuente, J Lonlac, B Kamsu-Foguem - Computers in Industry, 2024 - Elsevier
Artificial Intelligence (AI) is becoming fundamental in almost all activity sectors in our society.
However, most of the modern AI techniques (eg, Machine Learning–ML) have a black box …

The role of artificial intelligence algorithms in information systems research: a conceptual overview and avenues for research

D Bendig, A Bräunche - Management Review Quarterly, 2024 - Springer
Artificial intelligence (AI) has made remarkable progress in the past decade. Despite the
plethora of AI research, we lack an accrued overview of the extent to which management …

Customer Acquisition via Explainable Deep Reinforcement Learning

Y Song, W Wang, S Yao - Information Systems Research, 2024 - pubsonline.informs.org
Effective customer acquisition heavily hinges on sequential targeting to ensure that
appropriate marketing messages reach customers. Sequential targeting could guide …

Feedback loops in machine learning: A study on the interplay of continuous updating and human discrimination

K Bauer, R Heigl, O Hinz, M Kosfeld - Journal of the Association for …, 2024 - aisel.aisnet.org
Abstract Machine learning (ML) models often endogenously shape the data available for
future updates. This is important because of their role in influencing human decisions, which …

Predicting instructor performance in online education: An interpretable hierarchical transformer with contextual attention

W Wang, M Zhou, B Li, H Zhuang - Forthcoming at Information …, 2023 - papers.ssrn.com
Online education is a vital consumer industry that is undergoing rapid technological change.
This paper develops a deep learning model to predict instructor performance on online …

基于规则集成的可解释机器学习算法及应用.

闵继源, 鲁统宇, 任婷婷… - Journal of Frontiers of …, 2024 - search.ebscohost.com
机器学习算法因其良好的预测性能已经取得了巨大的成功, 但在对模型可解释性有着较高需求的
领域, 其适用性受到了限制. 针对机器学习算法缺乏可解释性的缺点, 基于规则集成思想提出一种 …

[PDF][PDF] Optimal Comprehensible Targeting

WW Zhang - 2023 - marketing.wharton.upenn.edu
Developments in machine learning and big data allow firms to fully personalize and target
their marketing mix. However, data and privacy regulations, such as those in the European …

Designing Explainable Predictive Machine Learning Artifacts: Methodology and Practical Demonstration

G Welsch, P Kowalczyk - arXiv preprint arXiv:2306.11771, 2023 - arxiv.org
Prediction-oriented machine learning is becoming increasingly valuable to organizations, as
it may drive applications in crucial business areas. However, decision-makers from …

Beyond Proximity: Network Location Features and Store Performance in Retail Agglomeration

C He - Available at SSRN 4738056, 2024 - papers.ssrn.com
Location selection has been an important decision for small retailers, yet empirical research
examining the relationship between store location and retail performance remains notably …