Heterogeneous valuation and eco-efficiency of Laser Land Leveling in paddy production in the Mekong Delta

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Dataset information

Country of origin
Updated
2026.03.05 08:45
Created
2025.02.11
Available languages
English
Keywords
eco-efficiency, ekoeffektivitet
Quality scoring

Dataset description

This dataset surveys the demand for land leveling by laser (LLL) services of the paddy growing farmers in the Mekong Delta provinces, Vietnam. Demographic characteristics of farmers, cultivated area, characteristics of land plot and rice cultivation process of households were reported. Using the auction method, farmers chose different levels of willingness to pay (WTP) for LLL service rental for each rice plot. The data represents for factors affecting WTP level were also collected to obtain necessary information for random control trial (RCT) research. We also collected the data on the rice cultivation regarding yield and inputs in the year from 2019 to 2022. Vietnam, has been the second largest rice exporter in the world with 14% of global rice export volume in 2021. The impacts of climate change are regarded as the most significant challenge to agricultural production in Vietnam, especially for paddy production, as the country ranks sixth among the top 10 most at-risk nations globally. Besides, Vietnamese rice farmers encounter challenges of low productivity, fragmented cultivation areas, and inefficient use of inputs. The reduction in rice cultivation areas is projected to continue in Vietnam and other Asian countries Therefore, there is an urgent need to promote the adoption of sustainable agricultural technologies to ensure resilient and sustainable agricultural systems, particularly in paddy cultivation, amid a changing climate. The rising prevalence of land fragmentation, especially in developing regions, introduces new challenges that remain largely unexplored. This dataset was collected to investigate how land fragmentation influences demand for precision agricultural technology and the policy challenges regarding fragmented landscapes.
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