Providing insight on decisions to hunt and trade bushmeat can facilitate improved management interventions that typically include enforcement, alternative employment, and donation of livestock. Conservation interventions to regulate bushmeat hunting and trade have hitherto been based on assumptions of utility- (i.e., personal benefits) maximizing behavior, which influences the types of incentives designed. However, if individuals instead strive to minimize regret, interventions may be misguided. We tested support for 3 hypotheses regarding decision rules through a choice experiment in Tanzania. We estimated models based on the assumptions of random utility maximization (RUM) and pure random regret maximization (P-RRM) and combinations thereof. One of these models had an attribute-specific decision rule and another had a class-specific decision rule. The RUM model outperformed the P-RRM model, but the attribute-specific model performed better. Allowing respondents with different decision rules and preference heterogeneity within each decision rule in a class-specific model performed best, revealing that 55% of the sample used a P-RRM decision rule. Individuals using a P-RRM decision rule responded less to enforcement, salary, and livestock donation than did individuals using the RUM decision rule. Hence, 3 common strategies, enforcement, alternative income-generating activities, and providing livestock as a substitute protein, are likely less effective in changing the behavior of more than half of respondents. Only salary elicited a large (i.e. elastic) response, and only for one RUM class. Policies to regulate the bushmeat trade based solely on the assumption of individuals maximizing utility, may fail for a significant proportion of the sample. Despite the superior performance of models that allow both RUM and P-RRM decision rules there are drawbacks that must be considered before use in the Global South, where very little is known about the social-psychology of decision making.

中文翻译：

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选择实验中决策规则对狩猎和丛林肉贸易的影响

深入了解狩猎和贸易丛林肉的决策可以促进改进管理干预措施，这些干预措施通常包括执法、替代就业和牲畜捐赠。迄今为止，监管丛林肉狩猎和贸易的保护干预措施是基于效用（即个人利益）最大化行为的假设，这会影响所设计的激励类型。然而，如果个人反而努力将后悔最小化，干预可能会被误导。我们通过坦桑尼亚的选择实验测试了对 3 个关于决策规则的假设的支持。我们基于随机效用最大化 (RUM) 和纯随机后悔最大化 (P-RRM) 及其组合的假设来估计模型。其中一个模型具有特定于属性的决策规则，另一个具有特定于类的决策规则。RUM 模型优于 P-RRM 模型，但特定于属性的模型表现更好。允许在特定类别模型中的每个决策规则内具有不同决策规则和偏好异质性的受访者表现最佳，表明 55% 的样本使用了 P-RRM 决策规则。与使用 RUM 决策规则的个人相比，使用 P-RRM 决策规则的个人对执法、工资和牲畜捐赠的反应较少。因此，执法、替代性创收活动和提供牲畜作为替代蛋白质这 3 种常见策略在改变超过一半受访者的行为方面可能不太有效。只有工资引起了大的（即弹性的）反应，并且仅适用于一个 RUM 类。仅基于个人效用最大化的假设来规范丛林肉贸易的政策可能会在很大一部分样本中失败。尽管允许 RUM 和 P-RRM 决策规则的模型性能优越，但在全球南方使用之前必须考虑一些缺点，那里对决策的社会心理学知之甚少。