Version 1
: Received: 9 July 2024 / Approved: 10 July 2024 / Online: 11 July 2024 (09:52:55 CEST)
How to cite:
Shi, X.; Zhang, Y.; Yu, M.; Zhang, L. Market Crisis Management Strategy Based on Predicting Loyal Customers Using Deep Meta-Learning. Preprints2024, 2024070868. https://doi.org/10.20944/preprints202407.0868.v1
Shi, X.; Zhang, Y.; Yu, M.; Zhang, L. Market Crisis Management Strategy Based on Predicting Loyal Customers Using Deep Meta-Learning. Preprints 2024, 2024070868. https://doi.org/10.20944/preprints202407.0868.v1
Shi, X.; Zhang, Y.; Yu, M.; Zhang, L. Market Crisis Management Strategy Based on Predicting Loyal Customers Using Deep Meta-Learning. Preprints2024, 2024070868. https://doi.org/10.20944/preprints202407.0868.v1
APA Style
Shi, X., Zhang, Y., Yu, M., & Zhang, L. (2024). Market Crisis Management Strategy Based on Predicting Loyal Customers Using Deep Meta-Learning. Preprints. https://doi.org/10.20944/preprints202407.0868.v1
Chicago/Turabian Style
Shi, X., Manning Yu and Lihao Zhang. 2024 "Market Crisis Management Strategy Based on Predicting Loyal Customers Using Deep Meta-Learning" Preprints. https://doi.org/10.20944/preprints202407.0868.v1
Abstract
Market crises pose significant challenges for businesses, emphasizing the importance of effective crisis management strategies. Central to these strategies is the ability to identify and retain loyal customers, who often serve as the bedrock of stability during tumultuous times. This paper investigates the application of deep meta-learning analysis to predict loyal customers as a cornerstone of market crisis management. Drawing upon an extensive literature review, the study explores previous research on market crises, customer loyalty, and the evolution of deep learning and meta-learning in crisis management contexts. Methodologically, the paper outlines data collection, model development, and evaluation procedures tailored for deep meta-learning-based customer prediction. In results, the overall accuracy of model 85%, a precision 0.88, recall 0.82, and F1-score 0.85 were obtained. The analysis demonstrates the effectiveness of deep meta-learning models in accurately identifying loyal customers during market crises, offering insights into their performance and applicability compared to traditional methods. Practical implications include potential applications in crisis management for businesses and considerations for real-world implementation.
Keywords
market crisis; deep learning; prediction model
Subject
Business, Economics and Management, Business and Management
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
