Determinants of profitability in rice processing among women in Patigi, Kwara State, Nigeria

Rice processing is a vital economic activity for women in Patigi, Kwara State, Nigeria, providing employment and income opportunities. Rice processing activities, excluding milling, are traditionally performed by women in the study area. However, these women rice processors face various challenges that affect their profitability. This study examines the determinants of profitability among women rice processors in the study area. Multistage sampling was used in selecting 80 women rice processors for the survey. The analytical tools employed include descriptive statistics and regression analysis. The results from descriptive statistics revealed that most (75.6%) of the respondents were married, with a mean age of 36 years and 7years of processing experience. The results from regression analysis indicated that market access (0.031, p=0.002), cost of paddy per bag (-2.219E-5, p<0.001), and fixed costs (-1.746E-6, p=0.040) were statistically significant determinants of profitability, with an R-squared value of 0.729 and an F-ratio of 18.061 (p < 0.001). Specifically, the results indicate that a unit increase in market access is associated with a 3.2% increase in profitability, and equally a decrease of a unit of paddy cost could increase profitability by 11.87%. The findings suggest that improving market access, reducing costs, and providing training and capacity-building programs can enhance the profitability of women rice processors in Patigi. The study thus recommends training on marketing strategies, access to market information systems, bulk purchasing, and adopting cost-saving technologies to promote the growth of the rice processing industry in Nigeria.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-09-30
DOI
https://doi.org/10.5281/zenodo.17214711
Primary Topic
Genome Rearrangement Algorithms
Type
article
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article

Determinants of profitability in rice processing among women in Patigi, Kwara State, Nigeria

Zenodo (CERN European Organization for Nuclear Research)
Genome Rearrangement Algorithms
article

Determinants of profitability in rice processing among women in Patigi, Kwara State, Nigeria

article en

Abstract

Rice processing is a vital economic activity for women in Patigi, Kwara State, Nigeria, providing employment and income opportunities. Rice processing activities, excluding milling, are traditionally performed by women in the study area. However, these women rice processors face various challenges that affect their profitability. This study examines the determinants of profitability among women rice processors in the study area. Multistage sampling was used in selecting 80 women rice processors for the survey. The analytical tools employed include descriptive statistics and regression analysis. The results from descriptive statistics revealed that most (75.6%) of the respondents were married, with a mean age of 36 years and 7years of processing experience. The results from regression analysis indicated that market access (0.031, p=0.002), cost of paddy per bag (-2.219E-5, p<0.001), and fixed costs (-1.746E-6, p=0.040) were statistically significant determinants of profitability, with an R-squared value of 0.729 and an F-ratio of 18.061 (p < 0.001). Specifically, the results indicate that a unit increase in market access is associated with a 3.2% increase in profitability, and equally a decrease of a unit of paddy cost could increase profitability by 11.87%. The findings suggest that improving market access, reducing costs, and providing training and capacity-building programs can enhance the profitability of women rice processors in Patigi. The study thus recommends training on marketing strategies, access to market information systems, bulk purchasing, and adopting cost-saving technologies to promote the growth of the rice processing industry in Nigeria.

Zenodo (CERN European Organization for Nuclear Research)
Decent work and economic growth
Openalex Percentile: Top 37%
Genome Rearrangement Algorithms
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