Authors :
Sujan Chandra Bhowmiik; Md. Monarul Islam; Mohammad Nazmul Haque Bhuiyan; Md. Selim Reza; Mohshi-U-Nahidy Islam
Volume/Issue :
Volume 9 - 2024, Issue 9 - September
Google Scholar :
https://tinyurl.com/mr25r6wz
Scribd :
https://tinyurl.com/yc2c8nzy
DOI :
https://doi.org/10.38124/ijisrt/IJISRT24SEP1328
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
The primary goal of this research is to assess
the impact of the Grains Trading Projects' Post-Harvest
Support Program on farmers' income. The research
took place in districts of Mymensingh, Natore, Bogura
& Dinajpur. Through the use of stratified random
sampling, a total of 374 recipients were selected to
constitute the study's sample. The research analyzed
eleven distinct characteristics of the recipients as
independent factors, unaffected by other variables, with
the respondents income change during project activities
being the dependent variable. Data was gathered from
the participants through a meeting conducted in person.
More than half (54.28%) of beneficiaries belonged to
medium and high income change compared to 45.19%
belong to low change income categories respectively.
The research results indicated that out of the 11
variables examined, a total of 6 independent variables
including land size, savings deposit, loan received, loan
utilization, training received, and project participation,
were found to have significant correlations (at the 0.5%
and 1% level) with the dependent variable. The study
revealed that six out of the 11 variables including land
size, savings deposit, loan received, loan utilization,
training received, and project participation showed
significant correlation (0.5% and 1%) with the
dependent variable. The correlation coefficient (r) is
0.370 and the coefficient of determination (R2) is 0.173
indicating that the combination of independent
variables contributes to 17.30% of the total income
change among respondents.
Keywords :
Post-Harvest Farmer, Chang Income; Development; Project; Beneficiaries, Proverty Alleviation.
References :
- World Bank. (2023). GNI per capita, Atlas method (current US$) - Bangladesh. Available online: https://data.worldbank.org/indicator/NY.GNP.PCAP.CD?locations=BD [Accessed on 29 July 2024].
- United Nations. (2023). World Population Prospects 2023 -Bangladesh. Available online: https://population.un. org/wpp/ [accessed on 11 August 2024].
- World Bank. (2019). Reducing Post-Harvest Losses and Enhancing Market Access in Rural Bangladesh. Available, online: https://www.worldbank.org/en/ country/bangladesh. [Accessed on 11 August 2024].
- Bangladesh Bureau of Statistics. (2019): BBS reports that agriculture remains the largest source of employment in rural Bangladesh, employing about 40% of the labor force. Source: BBS. (2019). Bangladesh Economic Review 2019. Available at: http://bbs.gov.bd [Accessed on 12 August 2024].
- Bangladesh Bureau of Statistics. (2019). Agricultural Census 2019. Available online: http://bbs.gov.bd [Accessed on 11 August 2024].
- IFAD. (2019). Post-Harvest Management Challenges in Rural Bangladesh. Available online: https://www.ifad.org/en/web/operations/country/id/bangladesh [Accessed on 16 August 2024].
- FAO. (2017). Reducing Post-Harvest Losses: Challenges and Opportunities in Bangladesh's Agricultural Sector. Available online: http://www.fao.org. [Accessed on 11 August 2024].
- World Bank. (2019). Improving Market Access for Smallholder Farmers in Bangladesh. Available online: https://www.worldbank.org. [Accessed on 10 August 2024].
- IFAD. (2018). Access to Finance and Agricultural Development in Bangladesh. Available online: https://www.ifad.org/en/web/operations/country/id/bangladesh. [Accessed on 11 August 2024].
- Bangladesh Agricultural Development Corporation (BADC). (2020). Annual Report on Agricultural Value Chain and Market Access. Available online: http://www.badc.gov.bd. [Accessed on 11 August 2024].
- MaCorr Sample Size Calculator. https://www.macorr. com/sample-size-calculator.htm [Accessed on 11 August 2024].
The primary goal of this research is to assess
the impact of the Grains Trading Projects' Post-Harvest
Support Program on farmers' income. The research
took place in districts of Mymensingh, Natore, Bogura
& Dinajpur. Through the use of stratified random
sampling, a total of 374 recipients were selected to
constitute the study's sample. The research analyzed
eleven distinct characteristics of the recipients as
independent factors, unaffected by other variables, with
the respondents income change during project activities
being the dependent variable. Data was gathered from
the participants through a meeting conducted in person.
More than half (54.28%) of beneficiaries belonged to
medium and high income change compared to 45.19%
belong to low change income categories respectively.
The research results indicated that out of the 11
variables examined, a total of 6 independent variables
including land size, savings deposit, loan received, loan
utilization, training received, and project participation,
were found to have significant correlations (at the 0.5%
and 1% level) with the dependent variable. The study
revealed that six out of the 11 variables including land
size, savings deposit, loan received, loan utilization,
training received, and project participation showed
significant correlation (0.5% and 1%) with the
dependent variable. The correlation coefficient (r) is
0.370 and the coefficient of determination (R2) is 0.173
indicating that the combination of independent
variables contributes to 17.30% of the total income
change among respondents.
Keywords :
Post-Harvest Farmer, Chang Income; Development; Project; Beneficiaries, Proverty Alleviation.