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4.3.2 Behavioral Heterogeneity
Recognizing that environmental and social changes may cause people to respond in
different ways is important in accurately accounting for human behavior and adaptation in FEW systems. Allowing for behavioral heterogeneity recognizes that
individuals may have different motivations for their actions and that how they react
to changes in their social or natural environments (e.g., due to policy changes, climate change, etc.) may also be different.
Models that incorporate behavioral heterogeneity can be complex, and may
therefore be more computationally difficult than those that model the behavior of a
single representative agent. However, methods have been developed that allow for
this heterogeneity in agents’ decision-making strategies, and that can incorporate
interactions between different agent types.
Models that incorporate types of individuals with different decision rules (beyond
those based on profit maximization), and interactions between individuals, allow for
behavioral heterogeneity within a population. These models demonstrate that allowing for different decision rules and direct interaction between individuals has implications for environmental quality, such as resource depletion and pollution levels.
(See Jager et al. 2000 for a more detailed discussion of incorporating heterogeneity
in models of human behavior.)
van Duinen et al. (2015) provide an example of the potential implications of
introducing behavioral heterogeneity in FEW systems research. They use an agentbased model (ABM) to study farmers’ adoption of irrigation systems in response to
increased drought risk. Behavioral heterogeneity and social interaction are introduced into the model by including types of agents with different decision-making
strategies. Agents differ in what they consider when deciding whether to adopt irrigation technology and the degree to which they consider others’ adoption decisions.
The model simulates the effects of drought from climate change on regional agricultural income, adaptation rate, water demand, and behavioral strategies. The results
show that allowing for decision-making heterogeneity and interactions between
farmers results in slower adoption than when farmers’ decision-making is based
purely on expected profit maximization. See Sect. 4.4.3 for more discussion of the
use of ABMs in FEW systems research.
4.3.3 Technology Adoption
Given the essential role that new technologies play in improving resource efficiencies and reducing environmental impacts of human consumption, technology adoption can be a key component of human adaptation in FEW systems. However,
technology will be ineffective in improving FEW system sustainability without
widespread adoption. It is therefore critical to consider drivers of technology
adoption, such as consumer decision-making and the social impacts of technology
adoption, to reach a more complete understanding of the role that technology can
M. Doidge et al.
4.3.2 Behavioral Heterogeneity
Recognizing that environmental and social changes may cause people to respond in
different ways is important in accurately accounting for human behavior and adaptation in FEW systems. Allowing for behavioral heterogeneity recognizes that
individuals may have different motivations for their actions and that how they react
to changes in their social or natural environments (e.g., due to policy changes, climate change, etc.) may also be different.
Models that incorporate behavioral heterogeneity can be complex, and may
therefore be more computationally difficult than those that model the behavior of a
single representative agent. However, methods have been developed that allow for
this heterogeneity in agents’ decision-making strategies, and that can incorporate
interactions between different agent types.
Models that incorporate types of individuals with different decision rules (beyond
those based on profit maximization), and interactions between individuals, allow for
behavioral heterogeneity within a population. These models demonstrate that allowing for different decision rules and direct interaction between individuals has implications for environmental quality, such as resource depletion and pollution levels.
(See Jager et al. 2000 for a more detailed discussion of incorporating heterogeneity
in models of human behavior.)
van Duinen et al. (2015) provide an example of the potential implications of
introducing behavioral heterogeneity in FEW systems research. They use an agentbased model (ABM) to study farmers’ adoption of irrigation systems in response to
increased drought risk. Behavioral heterogeneity and social interaction are introduced into the model by including types of agents with different decision-making
strategies. Agents differ in what they consider when deciding whether to adopt irrigation technology and the degree to which they consider others’ adoption decisions.
The model simulates the effects of drought from climate change on regional agricultural income, adaptation rate, water demand, and behavioral strategies. The results
show that allowing for decision-making heterogeneity and interactions between
farmers results in slower adoption than when farmers’ decision-making is based
purely on expected profit maximization. See Sect. 4.4.3 for more discussion of the
use of ABMs in FEW systems research.
4.3.3 Technology Adoption
Given the essential role that new technologies play in improving resource efficiencies and reducing environmental impacts of human consumption, technology adoption can be a key component of human adaptation in FEW systems. However,
technology will be ineffective in improving FEW system sustainability without
widespread adoption. It is therefore critical to consider drivers of technology
adoption, such as consumer decision-making and the social impacts of technology
adoption, to reach a more complete understanding of the role that technology can
M. Doidge et al.