TY - JOUR
T1 - Interlinked driving factors for decision-making in sustainable coffee production
AU - Brenes-Peralta, Laura
AU - De Menna, Fabio
AU - Vittuari, Matteo
N1 - Publisher Copyright:
© The Author(s), under exclusive licence to Springer Nature B.V. 2022.
PY - 2024/2
Y1 - 2024/2
N2 - The coffee sector, one of the top-traded commodity groups worldwide, seeks to overcome its sustainability challenges through different cultural and technical practices, including shaded-coffee plantations, common in Central America and recognized as an opportunity to overcome such challenges. However, there is limited literature explaining the elements that influence decision-making processes for sustainable coffee production; therefore, this study aimed at identifying and modeling the factors driving this sector toward decisions for sustainable coffee practices. The Interpretive Structural Modeling (ISM) method allowed to represent a comprehensive model of the factors. In addition, a case study of six shaded-coffee farms using Life Cycle Assessment (LCA) and Environmental Life Cycle costing (E-LCC) provided a contextualized analysis. Main findings stress that the farm stage is the highest contributor to the cost and environmental impacts in green coffee production. Moreover, the model undertook outcomes of the LCA, E-LCC and literature reviews, detecting knowledge and costs as key driving factors for farmers’ decisions, followed by the certification schemes, policies and the cooperative system as elements that influence decisions. Emissions, biodiversity and climate change adaptation behave as linking factors, while the use of water resources is the most dependent factor. This research establishes a first model to understand and address the factors that influence how decisions are taken in small-coffee farms when moving toward more sustainable coffee production, opening opportunities for further research as well as improved and tailored policy interventions in similar contexts.
AB - The coffee sector, one of the top-traded commodity groups worldwide, seeks to overcome its sustainability challenges through different cultural and technical practices, including shaded-coffee plantations, common in Central America and recognized as an opportunity to overcome such challenges. However, there is limited literature explaining the elements that influence decision-making processes for sustainable coffee production; therefore, this study aimed at identifying and modeling the factors driving this sector toward decisions for sustainable coffee practices. The Interpretive Structural Modeling (ISM) method allowed to represent a comprehensive model of the factors. In addition, a case study of six shaded-coffee farms using Life Cycle Assessment (LCA) and Environmental Life Cycle costing (E-LCC) provided a contextualized analysis. Main findings stress that the farm stage is the highest contributor to the cost and environmental impacts in green coffee production. Moreover, the model undertook outcomes of the LCA, E-LCC and literature reviews, detecting knowledge and costs as key driving factors for farmers’ decisions, followed by the certification schemes, policies and the cooperative system as elements that influence decisions. Emissions, biodiversity and climate change adaptation behave as linking factors, while the use of water resources is the most dependent factor. This research establishes a first model to understand and address the factors that influence how decisions are taken in small-coffee farms when moving toward more sustainable coffee production, opening opportunities for further research as well as improved and tailored policy interventions in similar contexts.
KW - Coffee shade
KW - Costa Rica
KW - Decision model
KW - ISM
KW - Life cycle
KW - Sustainability
UR - http://www.scopus.com/inward/record.url?scp=85144860226&partnerID=8YFLogxK
U2 - 10.1007/s10668-022-02821-6
DO - 10.1007/s10668-022-02821-6
M3 - Artículo
AN - SCOPUS:85144860226
SN - 1387-585X
VL - 26
SP - 3297
EP - 3330
JO - Environment, Development and Sustainability
JF - Environment, Development and Sustainability
IS - 2
ER -