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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).

Determinants of adoption of CSATs and the adoption effects on NRI are analyzed by using a multinomial endogenous switching regression framework.

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.

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.

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.

The research aims to assess the relationship between ecological innovation, green productivity, sustainable development and agricultural productivity in Vietnam. The agricultural sector of Vietnam has been observed with new opportunities which have fostered its productivity and growth.

The study uses a range of methods where initially, the researcher used descriptive analysis, cointegration and unit root tests. Secondly, Quantile Autoregressive Distributed Lag (QARDL) is used to assess the short and long run effects. The QARDL methodology is employed to capture the relationship between variables. Through this approach, the researcher is able to examine the scale of the interaction between dependent and independent variables.

The unique findings drawn through statistical techniques are also a great addition to the context of literature related to Vietnam’s agricultural productivity. Practical insights can also not be denied as the study provides beneficial guidelines for Vietnam’s agricultural sector to refine agricultural productivity.

Scholars are advised to use strong literary techniques to overcome these limitations and give a more thorough investigation into the same ideas. The availability and dependability of data was one of the primary challenges in carrying out this study. Vietnam has made significant advances in the collection and documentation of agricultural data, but there might still be gaps in the availability of thorough and current data on ecological innovation, green production and sustainable development.

Vietnam’s unique socioeconomic, cultural and environmental features influence how ecological innovation, green productivity, sustainable development and agricultural production are interconnected. Consequently, consideration should be taken when applying the results to various scenarios.