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AbstractThis article reflects on the study of consumer-related emerging topics in the Journal of Consumer Research (JCR) and looks ahead to consider what the next generation of emergent issues might be that capture consumer researchers' attention and interest. Drawing on conversations with eminent scholars who have made major contributions to JCR by introducing emerging topics to our literature, the author (i) provides a commentary of past approaches to researching novel emerging topics, (ii) suggests some domains from which new emerging topics for consumer research can be sourced, such as new digital technologies (e.g., artificial intelligence) and major societal challenges (e.g., climate change, sustainability, and health), and (iii) offers guidance on how to approach research on important emerging topics.

Abstract
Consumers have become always on and constantly connected. Search costs have plummeted, individuals' abilities to digitally express themselves and their opinions increased, and the opportunities for superior business and market intelligence for companies have skyrocketed. This has given rise to more, richer, and new sources of consumer data that marketers can leverage, and has fueled the data-driven insights revolution in marketing. But there is more to come very soon. In marketing, we are quickly moving from the age of the connected consumer to the age of the augmented consumer. New technologies like wearable devices, smart sensors, consumer IoT devices, smart homes, and, critically, artificial intelligence ecosystems will not only connect, but will substantially and meaningfully augment the consumer in terms of their thoughts and behaviors. The biggest challenge for marketers will lie in how they approach marketing to this new type of consumer, particularly personal artificial intelligence ecosystems. This means marketing to algorithms, instead of people, and that is very different to how most marketing work is currently done.

Abstract
Online social networks are used by hundreds of millions of people every day, but little is known about their effect on behavior. In five experiments, the authors demonstrate that social network use enhances self-esteem in users who are focused on close friends (i.e., strong ties) while browsing their social network. This momentary increase in self-esteem reduces self-control, leading those focused on strong ties to display less self-control after browsing a social network. Additionally, the authors present evidence suggesting that greater social network use is associated with a higher body mass index and higher levels of credit card debt for individuals with strong ties to their social network. This research extends previous findings by demonstrating that social networks primarily enhance self-esteem for those focused on strong ties during social network use. Additionally, this research has implications for policy makers because self-control is an important mechanism for maintaining social order and well-being.

AbstractThis study examines the impact of shared decision-making on investor overconfidence. Data from 2,000 investors, 6,394 consumers, and 657 experimental participants shed light on whether consumers who engage in joint financial decision-making are less affected by investor overconfidence than those who decide on their own. The findings show that investors who jointly decide are substantially less overconfident. However, family- or friend-inclined interactions are more effective in reducing overconfidence than relying on a financial advisor. The current research theoretically argues and empirically shows that shared metaknowledge drives this diminishing effect by highlighting unknown aspects of a financial decision. Compared to providing investors with solutions, problem reformulation, validation, or legitimation, only metaknowledge consistently decreases overconfidence in joint financial decision-making. It is argued that the process of highlighting unknowns can explain why interactions with family and friends have a more pronounced impact on investor overconfidence than consulting a professional advisor. The study provides a feasible debiasing tool to consumers, financial institutions, and other financial service providers to decrease overconfidence by emphasizing unknown aspects of an investment toward improving the quality of a consumer's financial decisions under uncertainty.

Abstract
Social media offers brands the ability to gauge consumer reactions to marketing and brand crises. While social media listening has focused on aggregate patterns, consumers differ in how they react to a crisis faced by a particular brand. Analyzing consumer behavior for 39 brands pertaining to 77 brand crises through the lens of consumer posts on brands' Facebook pages, we find that consumers' prior online interactions with the brand and the nature of the brand crisis moderate the language they employ in their posts. Specifically, these factors affect the extent to which consumers express anger and the familiarity of their language. While consumers who have not engaged with the brand previously employ more familiar language and self-referencing following values-related crises compared to consumers who have interacted with the brand, these individuals express more anger after performance-related crises. In contrast, consumers who have previously interacted with the brand express more anger in the wake of values-related crises. We discuss the implications of our findings for brand managers using social media posts as a means of monitoring consumer perceptions.

Abstract
The effect of voice technology on how consumers search for information online is explored. Results from a field survey of consumer experiences with voice-assisted search, three controlled experiments involving dictated (vs. typed) Google searches, and a supplemental experiment (N = 10,385) find that vocalizing (vs. typing) a query leads consumers to provide more specific, detailed descriptions of what they are seeking, which in turn yield search results that they are more satisfied with. This occurs because consumers tend to be more concerned about communicating clearly when engaging with voice technology, which prompts them to think more about how they want to convey their query before saying it out loud (vs. typing it). This increased forethought leads consumers to provide more detailed descriptions of what they are searching for in vocalized queries, such as by including brand names and intended purposes of use. Finally, the increased specificity of vocalized (vs. typed) queries results in search returns that better satisfy consumers' search goals. Implications for research on consumer–technology interactions, as well as for marketers and consumers, are discussed.

Abstract
Consumers and marketers often post photos of experiential consumption online. While prior research has studied how human presence in social media images impacts viewers' responses, the findings are mixed. The present research advances the current understanding by incorporating viewers' need for self-identity into their response model. Six studies, including an analysis of field data (14,725 Instagram photos by a top travel influencer) and five controlled experiments, find that the presence (vs. absence) of another human in the photo of an identity-relevant experience (e.g., a vacation, a wedding) can lower viewers' liking and preference for the venue (i.e., the vacation destination, the wedding venue) in the photo. This effect is mediated by viewers' feelings of others' ownership of the venue and moderated by the relevance of the experience to the viewer's self-identity as well as the distinctiveness of the human in the photo. This research is the first to investigate the impact of human presence in shared photos through the lens of psychological ownership and the identity-signaling function of ownership. The findings offer practical insights into when marketers should avoid human presence in advertisements and how to mitigate the negative impact of human presence in online photos.

AbstractThis article suggests a theory-driven approach to address the managerial problem of distinguishing between real and fake reviews. Building on memory research and linguistics, we predict that when recollecting an authentic experience in a product review, people rely to a greater extent on episodic memory. By contrast, when writing a fictitious review, people do not have episodic memory available to them. Therefore, they must rely to a greater extent on semantic memory. We suggest that reliance on these different memory types is reflected in the language used in authentic and fictitious reviews. We develop predictions about five linguistic features characterizing authentic versus fictitious reviews. We test our predictions via a multi-method approach, combining computational linguistics, experimental design, and machine learning. We employ a large-scale experiment to derive a dataset of reviews, as well as two datasets containing reviews from online platforms. We also test whether an algorithm relying on our theory-driven linguistic features is context independent, relative to other benchmark algorithms, and shows better cross-domain performance when tested across datasets. By developing a theory that extends memory and psycholinguistics research to the realm of word of mouth, this work contributes to our understanding of how authentic and fictitious reviews are created.

Abstract
The difficulty of determining how many observations to collect is a source of inefficiency in consumer behavior research. Group sequential designs, which allow researchers to perform interim analyses while data collection is ongoing, could offer a remedy. However, they are scarcely used in consumer behavior research, probably owing to low awareness, perceived complexity, or concerns about the validity of this approach. This article offers a tutorial on group sequential designs and introduces Pre-Registered Interim Analysis Designs (PRIADs): A practical five-step procedure to facilitate the adoption of these designs in marketing. We show that group sequential designs can be easily adopted by marketing researchers, and introduce a companion app to help researchers implement them. We demonstrate multiple benefits of PRIADs for researchers engaged in confirmatory hypothesis testing: They facilitate sample size decisions, allow researchers to achieve a desired level of statistical power with a smaller number of observations, and help conduct more efficient pilot studies. We validate this cost-saving potential through a comprehensive re-analysis of 212 studies published in the Journal of Consumer Research, which shows that using PRIADs would have reduced participant costs by 20–29%. We conclude with a discussion of limitations and possible alternatives to PRIADs.

Abstract
Recent research has highlighted a difference in the way consumers approach choice sets. Some consumers focus on products' quality benefits (vertical differentiation): their selections are driven by the level of quality obtained relative to the price paid. Other consumers focus on products' taste benefits (horizontal differentiation): their selections are driven by acquiring personal tastes at favorable prices. This article aims to investigate how consumers' benefit focus, a continuum anchored by quality and taste, drives their preferences between retailers differing in pricing strategies. All else equal, consumers who focus on taste benefits will prefer EDLP stores (infrequent discounters), while consumers who focus on quality benefits will prefer Hi-Lo stores (frequent discounters). Findings from our experiments and an analysis of consumer panel data corroborate this relationship. This work also shows the mediating role of perceived value and the effect of several moderators: the strength of the price–quality relationship, the pattern of discounts, and cherry-picking costs.