Path Dependence, Lock-in and Breakthrough of Agro-industrial Clusters: A Case Study of the Flower and Plant Cluster of JiangDu in China
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. Throu...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2024-01-01
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| Series: | BIO Web of Conferences |
| Online Access: | https://www.bio-conferences.org/articles/bioconf/pdf/2024/61/bioconf_isaeb2024_01018.pdf |
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| Summary: | 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. |
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| ISSN: | 2117-4458 |