Determinants of adoption of climate-smart agriculture technologies in rice production in Vietnam

Nhat Lam Duyen Tran Roberto F. Rañola, Bjoern Ole Sander Wassmann Reiner Dinh Tien Nguyen Nguyen Khanh Ngoc Nong

Purpose In recent years, climate-smart agriculture (CSA) was introduced to Vietnam to enhance farmers’ resilience and adaptation to climate change. Among the climate-smart agricultural technologies (CSATs) introduced were water-saving techniques and improved stress tolerant varieties. This study aims to examine the determinants of farmers’ adoption of these technologies and the effects of their adoption on net rice income (NRI) in three provinces as follows: Thai Binh (North), Ha Tinh (Central) and Bac Lieu (South). Design/methodology/approach Determinants of adoption of CSATs and the adoption effects on NRI are analyzed by using a multinomial endogenous switching regression framework. Findings The results showed that gender, age, number of family workers, climate-related factors, farm characteristics, distance to markets, access to climate information, confidence on the know-how of extension workers, membership in social/agricultural groups and attitude toward risk were the major factors affecting the decision to adopt CSATs. However, the effects of these factors on the adoption of CSATs varied across three provinces. These technologies when adopted tend to increase NRI but the increase is much greater when these are combined. Practical implications It is important to consider first the appropriateness of the CSA packages to the specific conditions of the target areas before they are promoted. It is also necessary to enhance the technical capacity of local extension workers and provide farmers more training on CSATs. Originality/value This study is the first attempt to identify key determinants of adoption of CSATs either singly or in combination and the adoption effects on NRI in Vietnam.

Open Access 0 16 дек. 2019

Тип материала: Статья


Язык: EN

Ранее опубликовано

Clarivate Analytics
Данные о статье из базы данных Clarivate Analytics
Accession Number: WOS:000502693900001
Issue: n/a
Pages: n/a
Journal expected citations: 0.452381
Category expected citations: 0.7
Percentile in subject area: 100
Journal impact factor: 0.92

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