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<p>Climate-smart agriculture (CSA) is increasingly promoted as a response to climate change challenges in the agricultural sector. However, despite growing international research, there is limited empirical evidence on the behavioral drivers of CSA adoption in developing countries such as Iran, where context-specific vulnerabilities require further investigation. This study addresses this gap by applying the Extended Technology Acceptance Model (TAM) to explore farmers’ adoption of CSA in the Marun Basin of Khuzestan province. The research population was the households in four counties, including Behbahan, Aghajari, Omidieh, and Ramhormoz (N = 112,513). A sample of 384 was determined using Krejcie and Morgan’s (1970) table. Data were analyzed using SPSS26. Results indicated that intention to use CSA technologies (β = 0.562), perceived usefulness (β = 0.266), and perceived ease of use (β = 0.260) exerted the strongest effects on adoption. The findings highlight that strengthening farmers’ intention to adopt CSA is the most decisive factor for accelerating sustainable agricultural transitions, providing new insights for policymakers and planners seeking to enhance agricultural resilience under climate change.</p>

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Adoption of climate-smart agriculture among Iranian farmers based on an extended technology acceptance model

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月11日

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  • Nadia Bakhshoudehnia,
  • Homayoun Farhadian,
  • Mahsa Saadvandi,
  • Vahid Karimi

摘要

Climate-smart agriculture (CSA) is increasingly promoted as a response to climate change challenges in the agricultural sector. However, despite growing international research, there is limited empirical evidence on the behavioral drivers of CSA adoption in developing countries such as Iran, where context-specific vulnerabilities require further investigation. This study addresses this gap by applying the Extended Technology Acceptance Model (TAM) to explore farmers’ adoption of CSA in the Marun Basin of Khuzestan province. The research population was the households in four counties, including Behbahan, Aghajari, Omidieh, and Ramhormoz (N = 112,513). A sample of 384 was determined using Krejcie and Morgan’s (1970) table. Data were analyzed using SPSS26. Results indicated that intention to use CSA technologies (β = 0.562), perceived usefulness (β = 0.266), and perceived ease of use (β = 0.260) exerted the strongest effects on adoption. The findings highlight that strengthening farmers’ intention to adopt CSA is the most decisive factor for accelerating sustainable agricultural transitions, providing new insights for policymakers and planners seeking to enhance agricultural resilience under climate change.