Representing human decision-making in agent-based simulation models: Agroforestry adoption in rural Rwanda (Record no. 53622)

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fixed length control field 02345nam a2200265Ia 4500
003 - CONTROL NUMBER IDENTIFIER
control field MX-MdCICY
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250625162431.0
040 ## - CATALOGING SOURCE
Transcribing agency CICY
090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN)
Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) B-19497
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245 10 - TITLE STATEMENT
Title Representing human decision-making in agent-based simulation models: Agroforestry adoption in rural Rwanda
490 0# - SERIES STATEMENT
Volume/sequential designation Ecological Economics, 200, p.107529, 2022
520 3# - SUMMARY, ETC.
Summary, etc. Advancing the transition towards more sustainable agriculture requires policy interventions that support farmers' adoption of sustainable practices. Models can support policy-makers in developing and testing interventions. For these models to provide reliable support, their underlying assumptions need to reflect reality and hence adequately represent human decision-making. This study compares several approaches that represent human decision-making. The comparison is applied to farmers' decision to adopt agroforestry. An agent-based simulation model is calibrated to a case study in rural Rwanda, where socio-economic survey data was collected from 145 small-scale farmers. Of these farmers, 72 were randomly selected to participate in a role-playing game, during which the players decided about adopting agroforestry. The game was conducted to validate the tested decision-making approaches. The simulations show that the decision-making approaches predict significantly different agroforestry adoption rates. Compared with the role-playing game, the Theory of Planned Behaviour exhibits the highest validity. Rational choice theory and the econometric approach overestimate implementation. Bounded rationality approaches underestimate the share of adopters. The results highlight the importance of adequately representing farmers' adoption decisions in models for providing reliable forecasts and effective policy support.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element DECISION-MAKING
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element AGENT-BASED MODELLING
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element THEORY OF PLANNED BEHAVIOUR
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element RATIONAL CHOICE THEORY
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element BOUNDED RATIONALITY
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element AGROFORESTRY ADOPTION
700 12 - ADDED ENTRY--PERSONAL NAME
Personal name Noeldeke, B.
700 12 - ADDED ENTRY--PERSONAL NAME
Personal name Winter, E.
700 12 - ADDED ENTRY--PERSONAL NAME
Personal name Ntawuhiganayo, E. B.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://drive.google.com/file/d/14hMAcezzrKGyv6HnDRaYEuGcdS307zAh/view?usp=drivesdk">https://drive.google.com/file/d/14hMAcezzrKGyv6HnDRaYEuGcdS307zAh/view?usp=drivesdk</a>
Public note Para ver el documento ingresa a Google con tu cuenta: @cicy.edu.mx
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Source of classification or shelving scheme Clasificación local
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  Clasificación local     Ref1 CICY CICY Documento préstamo interbibliotecario 25.06.2025   B-19497 25.06.2025 25.06.2025 Documentos solicitados