Litchi is a traditional tree crop grown in Southern China. Sustainable development of the litchi industry is reliant on technology adoption by farmers. The top grafting technique allows for the introduction of new, quality litchi varieties. The fact that these new varieties ripen earlier or later than the traditional ones helps stabilize litchi prices. Selling new litchi varieties can increase farmers' incomes through higher prices of quality varieties and stabilizing prices by staggering the harvest periods. However, the rate of adoption of top grafting among farmers is low, and up till now, more than half of the litchi trees in China are still traditional litchi varieties. This study explores the factors that influence top grafting adoption by litchi farmers. Using primary data gathered by the China Agriculture Research System of Litchi and Longan (CARSLL) from 567 litchi farming households, a binary logit choice model is employed to determine the factors that influence adoption of litchi top grafting among litchi farmers. The results show that farmers owning larger litchi orchards are more likely to adopt top grafting compared to ones owning smaller orchards. Litchi information accumulation, including experience and training, significantly influences farmers' technology adoption levels. Moreover, a positive attitude toward technology also significantly influences technology adoption behaviours.

No abstract

No abstract

No abstract

China has been promoting garbage classification in its rural areas, yet it lacks financial appropriation and fiscal decentralization to support waste processing projects. Though the existing literature has suggested fiscal decentralization strategies between different local government levels, few of the studies ascertain garbage classification efficiency from a quantitative perspective. To bridge the gap, this study examines the optimal fiscal decentralization strategies for garbage classification. It uses an optimization model while considering decision makers’ requirements regarding the fund allocation amounts at different government levels and the classification ratios in villages as constraints and decisions, respectively. A three-stage heuristic algorithm is applied to determine optimal landfill locations and efficient classification ratios for the garbage processing system in rural China, with an analytical discussion on the propositions and properties of the model. Our analytical results suggest that 1) the theoretically optimal solution is conditionally achievable, 2) the applied algorithm can achieve the optimal solution faster when the relationship between governance costs and classification ratios reaches some mathematical conditions, and 3) there is always a potential for increasing the retained funds between different government levels or for reducing the total appropriation from the county government. The numerical experiment on a primary dataset from 12 towns and 143 villages in the Pingyuan county of Guangdong province, China, does not only affirm the qualitative results, but it also provides insights into the difficulties encountered during the implementation of the garbage classification policy in China’s rural areas.