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This research identifies how choice of an eco-product (e.g., low-energy LED light bulbs, biodegradable paper towels) influences downstream, environmentally responsible behavior. Eco-product choice either reinforces or undermines subsequent environmentally responsible behavior, and this effect is contingent on individual consumers’ preexisting environmental consciousness: among less environmentally conscious consumers, proenvironmental behavior is undermined; in contrast, highly environmentally conscious consumers display reinforcement of proenvironmental behavior. The authors reveal that these differential effects are driven by two discrete processes working in opposition: goal satiation drives licensing in the case of less environmentally conscious consumers, and prosocial self-perceptions drive reinforcement among highly conscious consumers. In addition, the authors identify a point-of-purchase intervention that mitigates the detrimental effects among less environmentally conscious consumers. Together, these results shed light on the downstream consequences of eco-product choice for consumers, with implications for the marketing and regulation of such products.

The present research demonstrates how consumer responses to negative and positive offers are influenced by whether the administering marketing agent is an Artificial Intelligence (AI) or a human. In the case of a product or service offer that is worse than expected, consumers respond better when dealing with an AI agent in the form of increased purchase likelihood and satisfaction. In contrast, for a better than expected offer, consumers respond more positively to a human agent. We demonstrate that AI agents, in comparison to human agents, are perceived to have weaker intentions when administering offers, which accounts for this effect. That is, consumers infer that AI agents lack selfish intentions in the case of an offer that favors the agent and lack benevolent intentions in the case of an offer that favors the customer, thereby dampening the extremity of consumer responses. Moreover, we demonstrate a moderating effect such that marketers may anthropomorphize AI agents to strengthen perceived intentions, providing an avenue to receive due credit from consumers when providing a better offer and mitigate blame when providing a worse offer. Potential ethical concerns with the use of AI to bypass consumer resistance to negative offers are discussed.

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The use of Artificial Intelligence (AI) has grown rapidly in the service industry and AI’s emotional capabilities have become an important feature for interacting with customers. The current research examines personal disclosures that occur during consumer interactions with AI and humans in service settings. We found that consumers’ lay beliefs about AI (i.e., a perceived lack of social judgment capability) lead to enhanced disclosure of sensitive personal information to AI (vs. humans). We identify boundaries for this effect such that consumers prefer disclosure to humans over AI in (i) contexts where social support (rather than social judgment) is expected and (ii) contexts where sensitive information will be curated by the agent for social dissemination. In addition, we reveal underlying psychological processes such that the motivation to avoid negative social judgment favors disclosing to AI whereas seeking emotional support favors disclosing to humans. Moreover, we reveal that adding humanlike factors to AI can increase consumer fear of social judgment (reducing disclosure in contexts of social risk) while simultaneously increasing perceived AI capacity for empathy (increasing disclosure in contexts of social support). Taken together, these findings provide theoretical and practical insights into tradeoffs between utilizing AI versus human agents in service contexts.