Machine learning in marketing: Recent progress and future research directions
Decision-making in marketing has changed dramatically in the past decade. Companies
increasingly use algorithms to generate predictions for marketing decisions, such as which …
increasingly use algorithms to generate predictions for marketing decisions, such as which …
Machine learning in marketing: Recent progress and future research directions: Editorial for the Special Issue “Machine Learning in Marketing”
Decision-making in marketing has changed dramatically in the past decade. Companies
increasingly use algorithms to generate predictions for marketing decisions, such as which …
increasingly use algorithms to generate predictions for marketing decisions, such as which …
Harnessing the power of real-time analytics and reverse ETL: Strategies for unlocking data-driven insights and enhancing decision-making
J George - Available at SSRN 4963391, 2023 - papers.ssrn.com
Abstract Information integration and real-time analysis, as a system of managing big data,
have become a critical capability for organizations to extract relevant information to make …
have become a critical capability for organizations to extract relevant information to make …
Predicting online customer purchase: The integration of customer characteristics and browsing patterns
Despite the relentless growth of online retail, e-commerce platforms still suffer from a low
purchase conversion rate. Researchers and practitioners have attempted to understand …
purchase conversion rate. Researchers and practitioners have attempted to understand …
Design science research in operations management: is there a single type?
G Bagni, M Godinho Filho, M Finne… - Production Planning & …, 2024 - Taylor & Francis
Although many authors claimed that Design Science Research (DSR) could bring new
insights to Operations Management (OM), this research method is still little used in OM …
insights to Operations Management (OM), this research method is still little used in OM …
TEE: Real-Time Purchase Prediction Using Time Extended Embeddings for Representing Customer Behavior
Real-time customer purchase prediction tries to predict which products a customer will buy
next. Depending on the approach used, this involves using data such as the customer's past …
next. Depending on the approach used, this involves using data such as the customer's past …
Profit-driven fusion framework based on bagging and boosting classifiers for potential purchaser prediction
Z Liu, Y Zhang, MZ Abedin, J Wang, H Yang… - Journal of Retailing and …, 2024 - Elsevier
Accurately identifying potential purchasers (PPers) is pivotal for enhancing an enterprise's
core competitiveness in a competitive market. Although existing research focused on …
core competitiveness in a competitive market. Although existing research focused on …
Customer purchase prediction in B2C e-business: A systematic review and future research agenda
Customer purchase prediction is increasingly recognized as a crucial marketing strategy in
B2C e-business, promising enhanced business profitability and customer satisfaction …
B2C e-business, promising enhanced business profitability and customer satisfaction …
[HTML][HTML] Me, Myself, and My AI: How artificial intelligence classification failures threaten consumers' self-expression
Drawing from AI classification experience and identity-based motivation frameworks, this
research explores the impact of AI classification failures on consumers' self-identification …
research explores the impact of AI classification failures on consumers' self-identification …
Perilaku konsumtif mahasiswa pendidikan ekonomi sebagai dampak perkembangan e-commerce
N Nurjannah, N Nurdiana… - Jurnal Pendidikan …, 2023 - ejournal.unesa.ac.id
Penelitian ini bertujuan untuk menganalisis perilaku konsumtif mahasiswa Pendidikan
Ekonomi Universitas Negeri Makassar pada E-Commerce. Penelitian ini merupakan …
Ekonomi Universitas Negeri Makassar pada E-Commerce. Penelitian ini merupakan …