Deep Learning and Supply Chain based Enterprise Strategic Marketing Operation Management System Construction

The present focus of supply chain management is on how to understand customer information, establish customer segmentation, and make corporate resource allocation rational under restricted resources in order to maintain steady development. This paper explores integrating deep learning with supply chain management to enhance strategic marketing operations. It introduces an evaluation index system using a five-dimensional balanced scorecard and proposes a performance evaluation model based on the LMBP algorithm for efficient network weight calculation and training. Empirical testing with T Mobile demonstrates the model’s effectiveness, achieving a 97.29% accuracy rate and over 93% empirical fit accuracy, highlighting its potential for optimizing strategic marketing operations.

Authors

Institutions

Publication Details

Journal
Scalable Computing Practice and Experience
Published
2025-04-01
DOI
https://doi.org/10.12694/scpe.v26i3.4354
Primary Topic
E-commerce and Technology Innovations
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Deep Learning and Supply Chain based Enterprise Strategic Marketing Operation Management System Construction

Xiaoteng Ma, L. Wang
Scalable Computing Practice and Experience
E-commerce and Technology Innovations
article

Deep Learning and Supply Chain based Enterprise Strategic Marketing Operation Management System Construction

Xiaoteng Ma, L. Wang
article en

Abstract

The present focus of supply chain management is on how to understand customer information, establish customer segmentation, and make corporate resource allocation rational under restricted resources in order to maintain steady development. This paper explores integrating deep learning with supply chain management to enhance strategic marketing operations. It introduces an evaluation index system using a five-dimensional balanced scorecard and proposes a performance evaluation model based on the LMBP algorithm for efficient network weight calculation and training. Empirical testing with T Mobile demonstrates the model’s effectiveness, achieving a 97.29% accuracy rate and over 93% empirical fit accuracy, highlighting its potential for optimizing strategic marketing operations.

Scalable Computing Practice and ExperienceVol. 26(3)
Jiaxing University (CN), Shandong Agricultural University (CN)
Openalex Percentile: Top 89%
E-commerce and Technology Innovations
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.