Farmers’ Intention to Climate Change Adaptation in Agriculture in the Red River Delta Biosphere Reserve (Vietnam): A Combination of Structural Equation Modeling (SEM) and Protection Motivation Theory (PMT)

The Anh Luu, An Thinh Nguyen, Quoc Anh Trinh, Pham Van Tuan, Ba Bien Le, Duc Thanh Nguyen, Quoc Nam Hoang, Ha T.T. Pham, The Kien Nguyen, Luu Van Nang and Luc Hens
Additional contact information
The Anh Luu: Central Institute for Natural Resources and Environmental Studies (CRES), Vietnam National University (VNU), Hanoi 10000, Vietnam
An Thinh Nguyen: University of Economics and Business, Vietnam National University (VNU), Hanoi 10000, Vietnam
Quoc Anh Trinh: University of Sciences, Vietnam National University (VNU), Hanoi 10000, Vietnam
Pham Van Tuan: Ministry of Natural Resources and Environment (MONRE), Hanoi 10000, Vietnam
Ba Bien Le: Institute of Geography, Vietnam Academy of Sciences and Technology (VAST), Hanoi 10000, Vietnam
Duc Thanh Nguyen: Institute of Geography, Vietnam Academy of Sciences and Technology (VAST), Hanoi 10000, Vietnam
Quoc Nam Hoang: Institute of Geography, Vietnam Academy of Sciences and Technology (VAST), Hanoi 10000, Vietnam
Ha T.T. Pham: University of Sciences, Vietnam National University (VNU), Hanoi 10000, Vietnam
The Kien Nguyen: University of Economics and Business, Vietnam National University (VNU), Hanoi 10000, Vietnam
Luu Van Nang: Ministry of Natural Resources and Environment (MONRE), Hanoi 10000, Vietnam
Luc Hens: Vlaamse Instelling voor Technologisch Onderzoek (VITO), 2400 Mol, Belgium

Sustainability, 2019, vol. 11, issue 10, 1-17

Abstract: Coastal communities living in the low delta areas of Vietnam are increasingly vulnerable to tropical storms and related natural hazards of global climate change. Particularly in the Red River Delta Biosphere Reserve (RRDBR), farmers change the crop structure and diversify agricultural systems to adapt to the changing climate. The paper deals with a quantitative approach combined with behavior theories and surveyed data to analyze farmers’ intention to climate change adaptation in agriculture. Based on the Protection Motivation Theory (PMT), seven constructs are developed to a questionnaire surveying 526 local farmers: risk perception, belief, habit, maladaptation, subjective norm, adaptation assessment, and adaptation intention. Structural Equation Modeling (SEM) is implemented to extract eight factors and to quantify the relationship between protective behavior factors with the adaptation intention of the surveyed farmers. Two bootstrap samples of sizes 800 and 1200 are generated to estimate the coefficients and standard errors. The SEM result suggests a regional and three local structural models for climate change adaptation intention of farmers living in the RRDBR. Farmers show a higher adaptation intention when they perceive higher climate risks threatening their physical health, finances, production, social relationships, and psychology. In contrast, farmers are less likely to intend to adapt when they are subject to wishful thinking, deny the climate risks, or believe in fatalism.

Keywords: intention; climate change adaptation; agriculture; Red River Delta Biosphere Reserve (RRDBR); Structural Equation Modeling (SEM); Protection Motivation Theory (PMT) (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)

Downloads: (external link)
https://www.mdpi.com/2071-1050/11/10/2993/pdf (application/pdf)
https://www.mdpi.com/2071-1050/11/10/2993/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:11:y:2019:i:10:p:2993-:d:234619

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().