Are nudging and pricing strategies on food purchasing behaviors equally effective for all? Secondary analyses from the Supreme Nudge virtual supermarket study

Abstract. Both disgust and disease-related images appear able to induce an innate immune response but it is unclear whether these effects are independent or rely upon a common shared factor (e.g., disgust or disease-related cognitions). In this study we directly compared these two inductions using specifically generated sets of images. One set was disease-related but evoked little disgust, while the other set was disgust evoking but with less disease-relatedness. These two image sets were then compared to a third set, a negative control condition. Using a wholly within-subject design, participants viewed one image set per week, and provided saliva samples, before and after each viewing occasion, which were later analyzed for innate immune markers. We found that both the disease related and disgust images, relative to the negative control images, were not able to generate an innate immune response. However, secondary analyses revealed innate immune responses in participants with greater propensity to feel disgust following exposure to disease-related and disgusting images. These findings suggest that disgust images relatively free of disease-related themes, and disease-related images relatively free of disgust may be suboptimal cues for generating an innate immune response. Not only may this explain why disgust propensity mediates these effects, it may also imply a common pathway.

Ultra-dense and highly heterogeneous network (HetNet) deployments make the allocation of limited wireless resources among ubiquitous Internet of Things (IoT) devices an unprecedented challenge in 5G and beyond (B5G) networks. The interactions among mobile users and HetNets remain to be analyzed, where mobile users choose optimal networks to access and the HetNets adopt proper methods for allocating their own network resource. Existing works always need complete information among mobile users and HetNets. However, it is not practical in a realistic situation where important individual information is protected and will not be public to others. This paper proposes a distributed pricing and resource allocation scheme based on a Stackelberg game with incomplete information. The proposed model proves to be more practical by solving the problem that important information of either mobile users or HetNets is difficult to acquire during the resource allocation process. Considering the unknowability of channel gain information, the follower game among users is modeled as an incomplete information game, and channel gain is regarded as the type of each player. Given the pricing strategies of networks, users will adjust their bandwidth requesting strategies to maximize their expected utility. While based on the sub-equilibrium obtained in the follower game, networks will correspondingly update their pricing strategies to be optimal. The existence and uniqueness of Bayesian Nash equilibrium is proved. A probabilistic prediction method realizes the feasibility of the incomplete information game, and a reverse deduction method is utilized to obtain the game equilibrium. Simulation results show the superior performance of the proposed method.