Issue |
BIO Web Conf.
Volume 142, 2024
2024 International Symposium on Agricultural Engineering and Biology (ISAEB 2024)
|
|
---|---|---|
Article Number | 01018 | |
Number of page(s) | 5 | |
Section | Agricultural Economic Engineering and Market Management | |
DOI | https://doi.org/10.1051/bioconf/202414201018 | |
Published online | 21 November 2024 |
Path Dependence, Lock-in and Breakthrough of Agro-industrial Clusters: A Case Study of the Flower and Plant Cluster of JiangDu in China
1 School of Architecture and Urban Planning, Nanjing University, Nanjing 210008, China
2 School of Lifelong Education, Nanjing University, Nanjing 210008, China
* Corresponding author: 58551112@qq.com
Agriculture is characterised by low technological relevance and high policy dependence, which makes it more likely to fall into inefficient lock-in during the evolutionary process. However, with the innovation of new technologies and knowledge, new paths adapting to market demand often appear. Through fieldwork and semi-structured interviews, this study investigated the flower and plant industry of Jiangdu in China and concluded that there are four main stages of path evolution in the agricultural industry. Paths are formed when the industry matches the market demand, and policy support is equally important. Enhanced policy support and knowledge dissemination among practitioners strengthen the industrial path. If there’s a mismatch between supply and demand, the industry will probably fall into inefficient lock-in, the stage where policy support is weakened, but knowledge innovation is likely to be sustained in certain branches. If some certain branches cater for new market demands, path breakthrough is likely to occur, and policy support may return. Moreover, innovative knowledge networks will also be further developed. These findings evidence that market, technology and institution are key drivers across the four stages of cluster development. This is also a reference point for the sustainable development of agro-industrial clusters.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.