Suchergebnisse

Abstract
Evidence from four studies shows that signing one's name influences consumption-related behavior in a predictable manner. Signing acts as a general self-identity prime that facilitates the activation of the particular aspect of a consumer's self-identity that is afforded by the situation, resulting in behavior congruent with that aspect. Our findings demonstrate that signing causes consumers to become more (less) engaged when shopping in a product domain they (do not) closely identify with (studies 1 and 2), to identify more (less) closely with in(out)-groups (study 3), and to conform more with (diverge more from) in(out)-groups when making consumption choices in preference domains that are relevant to signaling one's identity (study 4). We discuss the theoretical and practical implications of these findings.

Abstract
Using a sample of individuals who hold target retirement funds (TRFs), we examine how people use arithmetic to estimate their retirement age. We find a robust "zero" bias where investors have a strong preference for TRFs that end with zero compared to TRFs that end with five. The evidence is consistent that the bias is an outcome of people using imprecise arithmetic, specifically rounding up and down in the computational estimation required to estimate their retirement year. The zero bias manifests itself in people born in years ending between eight and two. Those born in zero- through two-ending years select TRFs that imply they intend to retire at 70, whereas those born in eight- and nine-ending years choose TRFs that imply retiring at 60. The choices can significantly lower or increase wealth by altering the contribution amounts and exposing investors to risk incompatible with their age profile. The bias is particularly costly for those who are risk averse and select later TRFs but is also most beneficial to risk-averse consumers who choose early TRFs. We experimentally confirm that the contribution rates are related to the TRF choices and that the use of imprecise mathematical rounding is implicated in the bias.

AbstractWhen consumers select bundles of goods, they may construct those sequentially (e.g., building a bouquet one flower at a time) or make a single choice of a prepackaged bundle (e.g., selecting an already-complete bouquet). Previous research suggested that the sequential construction of bundles encourages variety seeking. The present research revisits this claim and offers a theoretical explanation rooted in combinatorics and norm communication. When constructing a bundle, a consumer chooses among different choice permutations, but when selecting amongst prepackaged bundles, the consumer typically considers unique choice combinations. Because variety is typically overrepresented among permutations compared to combinations, certain consumers (in particular, those with similar attitudes toward items that could compose a bundle) are induced by these different numbers of pathways to variety to display more or less variety-seeking behavior. This is in part explained by the variety norms communicated by different choice architectures, cues most likely to be inferred and used by those who are indifferent between the potential bundle components and thus looking for guidance. Across 5 studies in the main text and 11 in the web appendix, this article tests this account and offers preliminary exploration of newly identified residual effects that the pathways-to-variety account cannot explain.

Abstract
Purchase decisions typically involve tradeoffs between attributes associated with desirability (e.g., quality) and feasibility (e.g., price). In this article, we examine how the decision context impacts consumers' preference between a high-desirability (HD) option and a high-feasibility (HF) alternative. Nineteen studies demonstrate a novel context effect, the "upscaling effect," whereby introducing a symmetrically dominated decoy option to a set (i.e., an option that is inferior compared to all alternatives in the set) leads to an increase in the choice share of the HD option. To account for the upscaling effect, we advance a two-stage model of consumer decision-making for decisions that involve tradeoffs between desirability and feasibility. According to our model, when the decision context provides a reason for choosing either option, such as when a decoy option is added to the set, consumers prioritize reasons that support choice of HD options over HF alternatives. Our model can explain the upscaling effect, as well as other findings reported in the literature, such as asymmetric attraction effects (Heath and Chatterjee 1995) and asymmetric sales promotion effects (Blattberg and Wisniewski 1989). Furthermore, the upscaling effect holds important managerial implications because it provides an effective way to increase sales of high-end products.

Abstract
This research shows that AI-based conversational interfaces can have a profound impact on consumer–brand relationships. We develop a conceptual model of verbal embodiment in technology-mediated communication that integrates three key properties of human-to-human dialogue—(1) turn-taking (i.e., alternating contributions by the two parties), (2) turn initiation (i.e., the act of initiating the next turn in a sequence), and (3) grounding between turns (i.e., acknowledging the other party's contribution by restating or rephrasing it). These fundamental conversational properties systematically shape consumers' perception of an AI-based conversational interface, their perception of the brand that the interface represents, and their behavior in connection with that brand. Converging evidence from four studies shows that these dialogue properties enhance the perceived humanness of the interface, which in turn promotes more intimate consumer–brand relationships and more favorable behavioral brand outcomes (greater recommendation acceptance, willingness to pay a price premium, brand advocacy, and brand loyalty). Moreover, we show that these effects are reduced in contexts requiring less mutual understanding between the consumer and the brand. This research highlights how fundamental principles of human-to-human communication can be harnessed to design more intimate consumer–brand interactions in an increasingly AI-driven marketplace.