Assessing the impact of socioeconomic factors on the business of fish farmers and traders: A case study from Mymensingh district, Bangladesh
Studying socioeconomic variables is crucial for identifying business opportunities in the fish farming and trading industries. The objective of this study is to investigate the socioeconomic characteristics, and the impact of key socioeconomic factors on the operations of fish farmers and traders in...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-01-01
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| Series: | Social Sciences and Humanities Open |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590291125005571 |
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| Summary: | Studying socioeconomic variables is crucial for identifying business opportunities in the fish farming and trading industries. The objective of this study is to investigate the socioeconomic characteristics, and the impact of key socioeconomic factors on the operations of fish farmers and traders in specific areas of Mymensingh district. Data collection was carried out through questionnaire surveys and purposive sampling, involving a range of fish farmers and traders and focusing on 13 socioeconomic indicators. This study applied descriptive statistics and Principal Component Analysis (PCA) to address a significant research gap concerning the lack of integrated analyses on how socioeconomic variables collectively influence the livelihood quality of fish farmers and traders in Mymensingh district. By examining these interrelated factors within a unified framework, the study provides a more comprehensive understanding that previous studies have often overlooked. PCA extraction and Socioeconomic Engagement Index (SEI) construction were applied to ensure methodological rigor and enhance the practical implications of the findings. The study reveals that most fish farmers and traders are aged 30–45 years and possess over 10 years of experience in fish marketing. PCA found five principal components which explain 63.4 % of total variance. PC1 was the dominant factor, explaining the highest proportion of variance. It was characterized by strong loadings from housing conditions (0.8), sanitary facilities (0.8), annual income (0.7), and education (0.5). Variables with loadings above the 0.5 threshold underscore the essential role of basic infrastructure and socioeconomic stability in shaping the livelihoods of fish farmers and traders. Housing conditions had the highest loading, making it the most significant contributor to PC1, highlighting the critical role of adequate housing as a key indicator of livelihood quality in this sector. The high SEI score of 0.9 further reflects a robust level of socioeconomic participation in fish farming and trading, largely driven by the components of PC1. Investing in better housing and sanitation can lead to immediate gains in health and well-being, while improving income and education supports long-term sustainability in aquaculture. However, the study's findings aim to enhance capacity building, improve the livelihoods of fish farmers and traders, and inform the creation of more effective policies for the fish farming and trading sector. |
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| ISSN: | 2590-2911 |