Research on the Mechanisms and Pathways for Industrial Transfer in Northwest China: An Integrated Ecological Perspective
- DOI
- 10.2991/978-94-6239-689-0_21How to use a DOI?
- Keywords
- industrial transfer; community succession; expansive adaptation; ecological thresholds; coupling mechanism; Northwest China
- Abstract
Industrial transfer in Northwest China faces a persistent dilemma between ecological conservation and economic development. Moving beyond traditional economic geography, this study integrates ecological theories of “community succession” and “expansive adaptation” to construct a unified analytical framework explaining both industrial cluster dynamics and agent adaptive behaviors. Using a Logistic coupling model, we quantitatively demonstrate a significant S-shaped growth relationship (R2=0.68) between industrial transfer ecological level and expansive adaptation capacity, revealing two critical carrying capacity thresholds at 0.3 and 0.7. This research uncovers mechanisms underlying industrial succession outcomes and provides a systematic decision-support framework—from “ecological diagnosis to stage assessment to pathway adaptation”—offering novel theoretical and practical solutions for green industrial transformation in ecologically fragile regions.
- Copyright
- © 2026 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Yulin Kang AU - Bingneng Luo AU - Zhilin Kang PY - 2026 DA - 2026/05/28 TI - Research on the Mechanisms and Pathways for Industrial Transfer in Northwest China: An Integrated Ecological Perspective BT - Proceedings of the 2026 2nd International Conference on Data Mining and Project Management (DMPM 2026) PB - Atlantis Press SP - 215 EP - 223 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6239-689-0_21 DO - 10.2991/978-94-6239-689-0_21 ID - Kang2026 ER -