Cluster-based aquaculture growth
As shown in Chapter 3, fish production appears to be largely clustered and the number of fish farmers, feed traders, and fish traders have all experienced rapid growth since 2008, roughly in the same magnitude. The first objective of this chapter is to quantify the trend of clustering. Based on the...
| Autores principales: | , , |
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| Formato: | Capítulo de libro |
| Lenguaje: | Inglés |
| Publicado: |
International Food Policy Research Institute
2019
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/146601 |
| _version_ | 1855529136577052672 |
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| author | Zhang, Xiaobo Chen, Qingqing Fang, Peixun |
| author_browse | Chen, Qingqing Fang, Peixun Zhang, Xiaobo |
| author_facet | Zhang, Xiaobo Chen, Qingqing Fang, Peixun |
| author_sort | Zhang, Xiaobo |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | As shown in Chapter 3, fish production appears to be largely clustered and the number of fish farmers, feed traders, and fish traders have all experienced rapid growth since 2008, roughly in the same magnitude. The first objective of this chapter is to quantify the trend of clustering. Based on the fish value chain survey and mesolevel primary data, we show that fish production has indeed become clustered over time. When a large number of actors work on the same sector in a limited area, the competition is inherently intense. A question arises: Why do people still want to co-locate to work on similar businesses? The cluster must create some collective efficiency, which offsets the adverse effect on profit margin due to strong competition (Schmitz 1995). Better access to market, easy learning from others, and labor pooling are the three most noted features of positive externalities in clusters (Marshall 1920). In developing countries, clustering can help to alleviate entrepreneurs’ financial constraints, a major limiting factor to private sector development, by lowering capital barriers to enter and providing trade credit for operation (Ruan and Zhang 2009; Ali, Peerlings, and Zhang 2014). |
| format | Book Chapter |
| id | CGSpace146601 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2019 |
| publishDateRange | 2019 |
| publishDateSort | 2019 |
| publisher | International Food Policy Research Institute |
| publisherStr | International Food Policy Research Institute |
| record_format | dspace |
| spelling | CGSpace1466012025-11-06T04:09:06Z Cluster-based aquaculture growth Zhang, Xiaobo Chen, Qingqing Fang, Peixun cluster sampling supply chains water management fish trade water aquaculture trade aquaculture growth fish farms As shown in Chapter 3, fish production appears to be largely clustered and the number of fish farmers, feed traders, and fish traders have all experienced rapid growth since 2008, roughly in the same magnitude. The first objective of this chapter is to quantify the trend of clustering. Based on the fish value chain survey and mesolevel primary data, we show that fish production has indeed become clustered over time. When a large number of actors work on the same sector in a limited area, the competition is inherently intense. A question arises: Why do people still want to co-locate to work on similar businesses? The cluster must create some collective efficiency, which offsets the adverse effect on profit margin due to strong competition (Schmitz 1995). Better access to market, easy learning from others, and labor pooling are the three most noted features of positive externalities in clusters (Marshall 1920). In developing countries, clustering can help to alleviate entrepreneurs’ financial constraints, a major limiting factor to private sector development, by lowering capital barriers to enter and providing trade credit for operation (Ruan and Zhang 2009; Ali, Peerlings, and Zhang 2014). 2019-08-10 2024-06-21T09:07:43Z 2024-06-21T09:07:43Z Book Chapter https://hdl.handle.net/10568/146601 en https://doi.org/10.2499/9780896293618 The making of a blue revolution in Bangladesh Open Access application/pdf International Food Policy Research Institute Zhang, Xiaobo; Chen, Qingqing; and Fang, Peixun. 2019. Cluster-based aquaculture growth. In The making of a blue revolution in Bangladesh: Enablers, impacts, and the path ahead for aquaculture. Rashid, Shahidur; Zhang, Xiaobo, (Eds.). Chapter 4 Pp. 57-76. Washington, DC: International Food Policy Research Institute (IFPRI). https://hdl.handle.net/10568/146601 |
| spellingShingle | cluster sampling supply chains water management fish trade water aquaculture trade aquaculture growth fish farms Zhang, Xiaobo Chen, Qingqing Fang, Peixun Cluster-based aquaculture growth |
| title | Cluster-based aquaculture growth |
| title_full | Cluster-based aquaculture growth |
| title_fullStr | Cluster-based aquaculture growth |
| title_full_unstemmed | Cluster-based aquaculture growth |
| title_short | Cluster-based aquaculture growth |
| title_sort | cluster based aquaculture growth |
| topic | cluster sampling supply chains water management fish trade water aquaculture trade aquaculture growth fish farms |
| url | https://hdl.handle.net/10568/146601 |
| work_keys_str_mv | AT zhangxiaobo clusterbasedaquaculturegrowth AT chenqingqing clusterbasedaquaculturegrowth AT fangpeixun clusterbasedaquaculturegrowth |