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Using consumption and reward simulations to create desire for plant-based foods

使用消费和奖励模拟来创造对植物性食品的渴望

基本信息

批准号：
ES/T011343/1
负责人：
Esther Papies
金额：
$ 55.75万
依托单位：
University of Glasgow
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2021
资助国家：
英国
起止时间：
2021 至无数据
项目状态：
未结题

来源：
https://gtr.ukri.org/projects?ref=ES%2FT011343%2F1
关键词：
Using consumption reward simulations create

项目摘要

The production of animal-based foods has a significant, negative impact on the environment. Compared to plant-based protein sources, such as beans and lentils, the production of beef and other red meat requires 20 times more land and emits 20 times more greenhouse gas emissions per unit of edible protein. To curb climate change and sustain the planet, consumers urgently need to shift towards more plant-based diets. Most food choices, however, are driven by expectations of taste, rather than sustainability, and plant-based foods are perceived as less tasty than meat-based foods. How can these perceptions be changed to promote sustainable, plant-based food choices? This project proposes that desire for plant-based foods can be enhanced by food descriptions that emphasise sensory features, eating context, and hedonic consequences. Such descriptions will trigger spontaneous simulations (i.e., re-experiences) of eating and enjoying a food, and therefore create rewarding expectancies and desire. Supporting this account, previous work has shown that people describe attractive foods in terms of sensory experiences, eating context, and hedonic enjoyment. Such descriptions, in turn, are associated with increased desire for a food. This suggests that people spontaneously simulate (re-experience) eating attractive food, and that this contributes to the desire to eat. In addition, our pilot work has shown that adding such simulation features to labels for plant-based foods increases attractiveness of these food. Here, we will build on these preliminary findings and develop and test a systematic strategy for labeling plant-based foods such that they trigger desire. In Work Package 1, we will systematically establish the simulation features that induce desire for a large number of existing dishes. In a task adapted from cognitive psychology, participants will list features of a large number of foods. We will ask different groups of participants to focus on specific kinds of features (e.g., sensory features, eating context, etc). We will assemble these features and their links with attractiveness ratings in a comprehensive data-base that we will make openly available and disseminate among stakeholders in the food industry. In Work Package 2, we will use this simulation feature database to create desire-inducing labels for plant-based foods. Based on ratings by plant-based food consumers and mainstream consumers, we will select features that fit a number of relatively novel plant-based foods. These foods will be selected in collaboration with our partner, the Better Buying Lab, who have a strong network of industry partners actively engaged in the shift toward plant-based diets. Then, we will use these features to create eating simulation food labels, and conduct experiments to test whether such labels increase desire by assessing eating simulations, desire, salivation, and purchase intentions, compared to control labels that don't include eating simulation features.Finally, Work Package 3 will examine whether eating simulation labels affect actual liking, and if they increase purchase intentions measured after consumption only if the product lives up to the expectations created by the label. Here, consumers will taste a plant-based food that is presented with an eating simulation label or a control label, and will report liking and purchase intentions. Half of consumers receive a tasty version of the product, and half of consumers receive an adapted, bland version. Assessing desire before and after tasting the food will allow us to examine the interplay between simulations and experiences, which will be informative for the psychology of desire more generally. Together, these studies will establish a detailed understanding of the role of simulations in desire for food, and show how simulation-inducing language can be used to boost desire. This will help to make the urgent the dietary shift needed to sustain the planet.

动物性食品的生产对环境有重大的负面影响。与以植物为基础的蛋白质来源（如豆类和扁豆）相比，牛肉和其他红肉的生产需要多20倍的土地，每单位食用蛋白质排放的温室气体排放量多20倍。为了遏制气候变化和维持地球，消费者迫切需要转向更多的植物性饮食。然而，大多数食物的选择是由对味道的期望驱动的，而不是可持续性，植物性食物被认为不如肉类食物美味。如何才能改变这些观念，以促进可持续的植物性食品选择？该项目提出，对植物性食物的渴望可以通过强调感官特征、饮食环境和享乐后果的食物描述来增强。这样的描述将触发自发的模拟（即，重新体验）吃和享受食物，因此产生回报的期望和欲望。支持这一说法的是，之前的研究表明，人们从感官体验、饮食环境和享乐享受的角度来描述有吸引力的食物。这样的描述反过来又与对某种食物的渴望增加有关。这表明人们会自发地模拟（重新体验）吃有吸引力的食物，这有助于产生吃的欲望。此外，我们的试点工作表明，在植物性食品的标签上添加这种模拟功能会增加这些食品的吸引力。在这里，我们将在这些初步发现的基础上，开发和测试一种系统的策略，为植物性食品贴上标签，从而引发人们的欲望。在Work Package 1中，我们将系统地建立诱导对大量现有菜肴的欲望的模拟特征。在一个根据认知心理学改编的任务中，参与者将列出大量食物的特征。我们将要求不同组的参与者专注于特定类型的特征（例如，感官特征，饮食环境等）。我们将把这些特征及其与吸引力评级的联系整合到一个全面的数据库中，我们将公开提供该数据库，并在食品行业的利益相关者之间传播。在工作包2中，我们将使用这个模拟特征数据库来创建植物性食品的诱导欲望标签。根据植物性食品消费者和主流消费者的评分，我们将选择适合一些相对新颖的植物性食品的特征。这些食品将与我们的合作伙伴更好的购买实验室合作选择，他们拥有强大的行业合作伙伴网络，积极参与向植物性饮食的转变。然后，我们将使用这些特征来创建饮食模拟食品标签，并进行实验，通过评估饮食模拟，欲望，唾液和购买意愿来测试这些标签是否会增加欲望，与不包括饮食模拟功能的对照标签相比。最后，工作包3将检查食用模拟标签是否会影响实际的喜好，以及只有在产品符合标签所创造的期望的情况下，它们是否会增加消费后的购买意图。在这里，消费者将品尝带有食用模拟标签或对照标签的植物性食品，并报告喜欢和购买意图。一半的消费者得到的是美味的产品，一半的消费者得到的是经过改良的、平淡的产品。在品尝食物之前和之后评估欲望将使我们能够检查模拟和体验之间的相互作用，这将为更普遍的欲望心理学提供信息。总之，这些研究将建立对模拟在食物欲望中的作用的详细理解，并展示如何使用模拟诱导语言来增强欲望。这将有助于使维持地球所需的饮食转变迫在眉睫。