Journal of the Academy of Marketing Science最新文献

Powerlessness is a prevalent experience in everyday life. Although research has indicated that consumption can restore a sense of power, it remains unclear how people cope with powerlessness when regaining power is impossible. We propose that in such circumstances nostalgia consumption can act as a coping strategy, and examine if so, then how and when powerlessness increases consumer preference for nostalgic products. Across eight studies (including three supplementary studies), we found that consumers preferred nostalgic products when they felt powerless more than when they felt powerful. Uncertainty about the future acted as the underlying mechanism, one that consumers could alleviate by consuming nostalgic products. When high-status and nostalgic products were both available and regaining power was therefore possible, consumers with higher self-acceptance still preferred nostalgic products, whereas ones with lower self-acceptance preferred high-status products.

The use of conversational agents (e.g., chatbots) to simplify or aid consumers’ purchase decisions is on the rise. In designing those conversational agents, a key question for companies is whether and when it is advisable to enable voice-based rather than text-based interactions. Addressing this question, this study finds that matching consumers’ communication modality with product type (speaking about hedonic products; writing about utilitarian products) shapes consumers’ choice and increases choice satisfaction. Specifically, speaking fosters a feeling-based verbalizing focus, while writing triggers a reason-based focus. When this focus matches consumers’ mindset in evaluating the product type, preference fluency increases, thereby enhancing choice satisfaction. Accordingly, the authors provide insights into managing interactions with conversational agents more effectively to aid decision-making processes and increase choice satisfaction. Finally, they show that communication modality can serve as a strategic tool for low-equity brands to better compete with high-equity brands.

Consumers seek out online user-generated content to inform their purchase decisions because they perceive content created by other consumers as more believable than marketing communications. This research provides a theory of consumer digital trust in which consumer trust in user-generated content requires a digital environment that minimizes consumer suspicion of misrepresented or missing content. The theory is supported with empirical evidence from a hierarchical meta-analysis of 128 effects from 19 online platforms over 19 years (2004–2022). Account verification features, which alleviate suspicions of misrepresented content creator identities, increase the effect of user-generated content on firm performance, but content-enhancing features, such as photo filters, that can prompt suspicion of misrepresented brand experiences, weaken this link. Content-removal features that can spark speculation of missing information in content creators’ historical content and platform moderation media, which creates questions about missing content in brand conversations, weaken the influence of some user-generated content.

How can marketers increase social media engagement? This research argues that a simple adjustment to the language used in brand messaging can help. Specifically, that marketers can increase social media engagement by using language that directs the attention of consumers to a discrepancy. A field study that analyzed the text of brand messages across 17 product categories found that consumers are more likely to interact with brands when their messages include words that direct attention to discrepancies between actual and desired states (e.g., words such as could, should, wish, want, and lacking). Controlled experiments reveal the mechanism underlying this effect. Specifically, that using language that directs attention to a discrepancy about the self makes messages seem more relevant, which, in turn, increases the likelihood that consumers will interact with the brand. This type of language is especially effective at making messages seem more relevant (and hence more engaging) among consumers that feel like they lack personal control in their lives. These findings provide marketers with a simple, yet theoretically-grounded technique for engaging more consumers with their brand messaging.

When a firm announces a product recall it typically incurs a market penalty in the form of a decline in its stock price. But a specific recall announcement often happens among recalls by other firms in the industry. Could recent recalls by other firms in the industry impact the market penalty for a new recall announcement? To capture and test this effect, the authors conceptualize recall environment intensity. Using salience theory, they identify the dimensions of the recall environment intensity construct, confirm these dimensions using interviews and a survey, and develop a measure for the construct. The authors then develop hypotheses for the effect of recall environment intensity on the stock penalty for a new recall announcement and propose boundary conditions for the effect. The hypotheses are tested using data from the automobile industry to show that a firm that announces a recall in a high intensity recall environment will have a smaller decline in stock price, though the effect varies with the reliability reputation of the brand and the age of the recalled products. The study provides a nuanced understanding of the stock market response to recall announcements and offers guidance on how to conceptualize and measure recall environment intensity.

Despite offering substantial opportunities to tailor services to consumers’ wants and needs, artificial intelligence (AI) technologies often come with ethical and operational challenges. One salient instance of such challenges emerges when vulnerable consumers, consumers who temporarily or permanently lack resource access or control, are unknowingly discriminated against, or excluded from the marketplace. By integrating the literature on consumer vulnerability, AI for social good, and the calls for rethinking marketing for a better world, the current work builds a framework on how to leverage AI technologies to detect, better serve, and empower vulnerable consumers. Specifically, our AID framework advocates for designing AI technologies that make services more accessible, optimize customer experiences and journeys interactively, and to dynamically improve consumer decision-making. Adopting a multi-stakeholder perspective, we also discuss the respective implications for researchers, managers, consumers, and public policy makers.

Much existing research in marketing examines theory using between-persons research designs, yet draws implications that are based on within-person causal logics. This mismatch is problematic in developing marketing knowledge, and in impacting marketing practice effectively. The present article discusses the importance of conducting within-person research in marketing, alongside suggesting marketing constructs that could benefit from within-person analyses. We provide details on how to conceptualize within-person theories, and compare them with the more common between-persons approach. Furthermore, a set of important methodological considerations and recommendations for designing within-person studies is elaborated on, and theoretical and empirical principles are applied to an empirical demonstration. The results show how theories and relationships can sometimes differ across levels, but in other instances can remain consistent. We draw out a set of important implications and directions for future marketing research, and encourage researchers to incorporate within-person approaches into their toolkit of theoretical and empirical methods.

Financial distress befalls even well-managed firms, many of which find ways to turn around. Hence, it is pertinent to explore how distressed firms recover. Unfortunately, extant research sheds little light on the role of marketing in enabling distressed firms’ turnaround. Using a longitudinal dataset of U.S. firms, we empirically show that when the source of distress is firm-specific, it is marketing capability (as opposed to R&D and operations capabilities) that enables a turnaround. However, when distress is industry-driven, R&D capability is also beneficial. Further, although operations capability and cost-reduction actions do help distressed firms survive, they do not help firms regain financial well-being. Overall, these results highlight the importance of capabilities in the context of distressed firms and have implications for both firm managers and shareholders.

In this research, we document knowledge gaps between consumers and experts about what consumer actions most effectively help mitigate climate change. We then identify three sources for lack of consumer knowledge on greenhouse gas emissions associated with consumption: carbon emissions labeling, awareness of indirect versus direct emissions, and orders of magnitude differences in carbon intensity across behaviors. We further propose that this lack of knowledge and several cognitive and motivational biases lead consumers away from effective climate actions, including the tendency to focus on first- versus second-order effects of “green” behaviors, motivated reasoning that easier, more accessible actions are more impactful, and a focus on individual behavior versus systemic changes. We close with a research agenda designed to address the lack of knowledge and biases we identify, while acknowledging that shifting marketers and consumers to focus on systemic changes may be both most challenging and most impactful.