Institute for Resources, Environment and Sustainability, University of British Columbia, Vancouver, BC, Canada.
African Climate & Development Initiative, University of Cape Town, Cape Town, South Africa.
Risk Anal. 2019 Aug;39(8):1755-1770. doi: 10.1111/risa.13290. Epub 2019 Mar 4.
Researchers in judgment and decision making have long debunked the idea that we are economically rational optimizers. However, problematic assumptions of rationality remain common in studies of agricultural economics and climate change adaptation, especially those that involve quantitative models. Recent movement toward more complex agent-based modeling provides an opportunity to reconsider the empirical basis for farmer decision making. Here, we reconceptualize farmer decision making from the ground up, using an in situ mental models approach to analyze weather and climate risk management. We assess how large-scale commercial grain farmers in South Africa (n = 90) coordinate decisions about weather, climate variability, and climate change with those around other environmental, agronomic, economic, political, and personal risks that they manage every day. Contrary to common simplifying assumptions, we show that these farmers tend to satisfice rather than optimize as they face intractable and multifaceted uncertainty; they make imperfect use of limited information; they are differently averse to different risks; they make decisions on multiple time horizons; they are cautious in responding to changing conditions; and their diverse risk perceptions contribute to important differences in individual behaviors. We find that they use two important nonoptimizing strategies, which we call cognitive thresholds and hazy hedging, to make practical decisions under pervasive uncertainty. These strategies, evident in farmers' simultaneous use of conservation agriculture and livestock to manage weather risks, are the messy in situ performance of naturalistic decision-making techniques. These results may inform continued research on such behavioral tendencies in narrower lab- and modeling-based studies.
长期以来，判断和决策研究人员一直驳斥我们是经济理性优化者这一观点。然而，在农业经济学和气候变化适应研究中，尤其是在涉及定量模型的研究中，仍普遍存在理性的有问题假设。最近，越来越倾向于采用更复杂的基于代理的建模方法，这为重新考虑农民决策的经验基础提供了机会。在这里，我们从根本上重新概念化农民的决策，使用现场心理模型方法来分析天气和气候风险管理。我们评估了南非的大型商业谷物种植者（n = 90）如何协调与他们每天管理的其他环境、农艺、经济、政治和个人风险相关的天气、气候变异性和气候变化决策。与常见的简化假设相反，我们表明，由于面临棘手和多方面的不确定性，这些农民往往会满足而不是优化；他们对有限的信息使用不完美；他们对不同的风险有不同的厌恶；他们在多个时间范围内做出决策；他们对变化的条件保持谨慎；他们多样化的风险认知导致个人行为的重要差异。我们发现，他们在普遍存在不确定性的情况下使用两种重要的非优化策略，我们称之为认知阈值和模糊对冲，以做出实际决策。这些策略在农民同时使用保护性农业和牲畜来管理天气风险的过程中显而易见，是自然决策技术在现场的混乱表现。这些结果可能会为在更狭隘的基于实验室和建模的研究中继续研究这种行为倾向提供信息。
