Department of Food and Resource Economics, University of Copenhagen, Rolighedsvej 1958, Building C, 1st floor, Frederiksberg C, Denmark.
Center for Macroecology, Evolution and Climate, University of Copenhagen, Universitetsparken 15, Building 3, 2nd floor, Østerbro, 2100, Denmark.
Conserv Biol. 2020 Dec;34(6):1393-1403. doi: 10.1111/cobi.13628.
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.
提供有关狩猎和交易丛林肉决策的见解,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,为规范丛林肉狩猎和贸易而采取的保护干预措施基于效用最大化(即个人利益)行为的假设,这影响了激励措施的设计类型。然而,如果个人反而努力将遗憾最小化,干预措施可能会产生误导。我们通过在坦桑尼亚进行选择实验,测试了 3 种关于决策规则的假设的支持。我们根据随机效用最大化(RUM)和纯粹随机后悔最大化(P-RRM)的假设以及它们的组合来估计模型。其中一个模型具有特定属性的决策规则,另一个模型具有特定类别的决策规则。RUM 模型的表现优于 P-RRM 模型,但特定属性的模型表现更好。允许具有不同决策规则和偏好异质性的受访者在特定类别模型中使用属性特定的决策规则表现最佳,这表明 55%的样本使用了 P-RRM 决策规则。与使用 RUM 决策规则的人相比,使用 P-RRM 决策规则的人对执法、工资和牲畜捐赠的反应较少。因此,3 种常见策略,即执法、替代创收活动以及提供牲畜作为替代蛋白质,可能在改变超过一半受访者的行为方面效果不佳。只有工资引起了较大的(即弹性)反应,而且只针对一个 RUM 类别。仅基于个人最大化效用的假设来制定规范丛林肉贸易的政策,可能会在很大一部分样本中失败。尽管允许同时使用 RUM 和 P-RRM 决策规则的模型表现出色,但在社会心理学决策方面知之甚少的南方国家,在使用这些模型之前,还必须考虑到一些缺点。