Rural residents' climate change perception and its influence on climate-smart business adoption using technology acceptance model: A study in Lahijan County, Iran

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Authors: Ali Akbar Barati, Hossein Shabanali Fami, Seyed Erfan Hosseini, Mohadeshe Aliakbari
Cited by: 1
References: 64

Abstract

Rural areas heavily rely on natural resources. This makes their residents and businesses vulnerable to the climate change and its impacts. Addressing these challenges requires reducing harmful climate effects, promoting adaptation, and improving rural-environmental relationships for sustainable development. This study aims to explore how rural residents perceive climate change influence their adoption of climate-smart rural businesses in northern Iran. Data were collected using a questionnaire from a sample include 175 rural residents selected from a population of 23,668. The partial least squares modeling method was employed to data analysis. Results showed that tangible natural impacts, such as rising soil salinity and poorer groundwater quality, most strongly shaped villagers’ perceptions of climate change. However, residents exhibited low trust in climate-smart rural businesses as effective solutions, indicating a confidence gap. Attitudes toward climate-smart rural businesses as the most important factor affecting adoption intention. The study highlights the need for policies that address trust gaps, enhance perceived usefulness and ease of climate-smart rural businesses to shift attitudes toward climate-smart rural businesses, and resolve urgent environmental challenges. It seems, integrating local perspectives with ecological and social realities is vital to align rural livelihoods with sustainability goals and ensure effective climate adaptation.

Fields of Study & Subjects

Technology Adoption and User Behaviour Economic Growth and Development Environmental Sustainability in Business

Publication details

Journal / source
Scientific African
Publisher
Elsevier BV
Volume
31
Pages
e03256–e03256
Publication date
14 February 2026
Language
EN