Research on the Transformation Paths of Traditional Enterprises in Jiujiang City in the Context of Intelligent Manufacturing

With the rapid development of new-generation information technologies, intelligent manufacturing has become a key direction for the transformation and upgrading of China’s manufacturing sector. As a major industrial city in Jiangxi Province, Jiujiang’s traditional enterprises face both policy opportunities and multifaceted challenges in terms of technology, talent, and management during their transformation. Against the backdrop of intelligent manufacturing, this paper reviews relevant theoretical foundations and existing research, analyzes the practical difficulties and developmental characteristics of traditional enterprises in Jiujiang, and constructs three typical transformation path models: “technology-driven,” “management-optimization,” and “collaborative-integration.” On this basis, the study proposes promoting high-quality intelligent transformation of regional enterprises through three approaches: government policy guidance, internal capability enhancement, and industry-university-research collaboration. The research findings offer both theoretical insight and practical guidance for local government policymaking and enterprise decision-making regarding transformation paths.

Authors

Institutions

Publication Details

Journal
Journal of improved oil and gas recovery technology.
Published
2025-06-30
DOI
https://doi.org/10.53469/wjimt.2025.08(06).17
Primary Topic
Regional Development and Environment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research on the Transformation Paths of Traditional Enterprises in Jiujiang City in the Context of Intelligent Manufacturing

Wei Zhu, Ping Ouyang, Mengnan Kong
Journal of improved oil and gas recovery technology.
Regional Development and Environment
article

Research on the Transformation Paths of Traditional Enterprises in Jiujiang City in the Context of Intelligent Manufacturing

Wei Zhu, Ping Ouyang, Mengnan Kong
article en

Abstract

With the rapid development of new-generation information technologies, intelligent manufacturing has become a key direction for the transformation and upgrading of China’s manufacturing sector. As a major industrial city in Jiangxi Province, Jiujiang’s traditional enterprises face both policy opportunities and multifaceted challenges in terms of technology, talent, and management during their transformation. Against the backdrop of intelligent manufacturing, this paper reviews relevant theoretical foundations and existing research, analyzes the practical difficulties and developmental characteristics of traditional enterprises in Jiujiang, and constructs three typical transformation path models: “technology-driven,” “management-optimization,” and “collaborative-integration.” On this basis, the study proposes promoting high-quality intelligent transformation of regional enterprises through three approaches: government policy guidance, internal capability enhancement, and industry-university-research collaboration. The research findings offer both theoretical insight and practical guidance for local government policymaking and enterprise decision-making regarding transformation paths.

Journal of improved oil and gas recovery technology.Vol. 8(6)
Jiujiang University (CN), Jiangxi University of Technology (CN)
Openalex Percentile: Top 79%
Regional Development and Environment
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.

Research on the Transformation Paths of Traditional Enterprises in Jiujiang City in the Context of Intelligent Manufacturing — Wei Zhu, Ping Ouyang, et al. · Journal of improved oil and gas recovery technology. (2025) | TGRS Research Map | TGRS