A Study Of Satisfaction And Challenges For Marginal And Small Farmers Towards Custom Hiring Centre Services In Jalgaon District.

Abstract

Custom hiring centres are crucial for marginal and small farmers because they provide access to expensive, modern agricultural machinery without outright purchase. These centres allow farmers to rent equipment on a need basis, which helps reduce the capital burden and enhance productivity. For small and marginal farmers, who often operate on thin margins and may not have the financial capability to invest in high-cost machinery, these centres enable them to adopt modern farming techniques, improve crop yields, and reduce labor costs. This arrangement also facilitates timely operations during critical farming periods, such as sowing and harvesting, potentially increasing farm income and sustainability. Overall, custom hiring centres play a vital role in leveling the playing field for smallholders by improving their access to technology and mechanization. The importance of satisfaction and challenges for marginal and small farmers towards Custom Hiring Centre Services is crucial in understanding their experiences and needs within the agricultural sector. High satisfaction levels, as seen with marginal farmers, can signify the effectiveness of these services in meeting their requirements, potentially leading to their continued usage and positive word-of-mouth referrals. Conversely, challenges that small farmers seem to face more significantly underscore areas where improvements and support are necessary to ensure that Custom Hiring Centres can effectively cater to their needs and alleviate their difficulties. Addressing these issues while maintaining or enhancing satisfaction levels among marginal farmers can contribute to a more equitable and efficient agricultural service ecosystem. The study is based on primary data collected from 120 farmers. A survey method is used for the collection of primary data. SPSS is used for the analysis of data. Descriptive and inferential statistics are used to study the objectives and validate the hypothesis.