The Lonely Reason Impeding Compliance with COVID-19 Prevention Guidelines

To reduce transmission of the 2019 coronavirus (COVID-19), the US Center for Disease Control recommends that all individuals follow a series of prevention guidelines (e.g., wearing a mask, physical distancing, and vigilant handwashing). However, some individuals have been unwilling to comply with them. In this research, we use reciprocal altruism theory to investigate the role of loneliness in compliance with COVID-19 prevention guidelines. Specifically, we find that lonely (vs. non-lonely) consumers report less willingness to comply with these guidelines. Process evidence demonstrates that this occurs because lonely individuals experience a lower sense of obligation to reciprocate. Importantly, the negative impact of loneliness on compliance with COVID-19 prevention guidelines can be offset through advertising messaging strategies when information about COVID-19 is framed using an agentic (vs. communal) advertising messaging. Thus, marketers may want to consider the important role of loneliness when tailoring messaging appeals that encourage compliance with COVID-19 prevention guidelines

When Not Belonging Means Bad News for the Planet: How a Low Sense of Belonging Diminishes the Value of Sustainable Products

Consumers increasingly report feeling disconnected from others. They live farther from family, belong to fewer social groups and are more likely to live alone than ever before (Pew Research Center 2015). A low sense of belonging is an aversive state for consumers, since relationships provide access to survival benefits such as resources and protection (Buss 1990). Consumers often use sustainable products to help them experience belonging since these products are typically more expensive than non-sustainable products and can signal that one is a good, cooperative group member who is willing to incur individual costs to maintain a group resource (e.g., the environment) (Griskevicius et al. 2010). However, we suggest that sustainable products lose their value when individuals feel like they do not belong, as these individuals cannot extract social benefits from the group such as elevated group status and increased access to resources within groups. Four experiments test this assertion while providing process evidence and boundary conditions for the proposed effect. Experiment 1 demonstrates that individuals lower in their sense of belonging evaluate sustainable products less favorably than those higher in their sense of belonging. Experiment 2 provides process evidence to show that this effect occurs as a low sense of belonging triggers a focus away from others and leads to less concern for social acceptance when making sustainable purchases. Experiments 3 and 4 find that the negative impact of low belonging on sustainable products is eliminated when the social aspect of the product is removed. These results suggest that marketers must account for consumers’ willingness to incur the costs of participating in sustainable behaviors, especially among consumers low in belonging

Temporal-Difference Reinforcement Learning with Distributed Representations

Temporal-difference (TD) algorithms have been proposed as models of reinforcement learning (RL). We examine two issues of distributed representation in these TD algorithms: distributed representations of belief and distributed discounting factors. Distributed representation of belief allows the believed state of the world to distribute across sets of equivalent states. Distributed exponential discounting factors produce hyperbolic discounting in the behavior of the agent itself. We examine these issues in the context of a TD RL model in which state-belief is distributed over a set of exponentially-discounting “micro-Agents”, each of which has a separate discounting factor (γ). Each µAgent maintains an independent hypothesis about the state of the world, and a separate value-estimate of taking actions within that hypothesized state. The overall agent thus instantiates a flexible representation of an evolving world-state. As with other TD models, the value-error (δ) signal within the model matches dopamine signals recorded from animals in standard conditioning reward-paradigms. The distributed representation of belief provides an explanation for the decrease in dopamine at the conditioned stimulus seen in overtrained animals, for the differences between trace and delay conditioning, and for transient bursts of dopamine seen at movement initiation. Because each µAgent also includes its own exponential discounting factor, the overall agent shows hyperbolic discounting, consistent with behavioral experiments