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An editorial is presented in which the authors consider the effects of artificial intelligence (AI) on scholarly publishing, with particular focus given to consumer research. Topics of discussion include digitization of consumer research practice, questions surrounding the use of GenAI during the research process, the use of GenAI as a support tool in editorship, and human adoption of AI.

This 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 FROM AUTHOR]

Marketers are adopting increasingly sophisticated ways to engage with customers throughout their journeys. We extend prior perspectives on the customer journey by introducing the role of digital signals that consumers emit throughout their activities. We argue that the ability to detect and act on consumer digital signals is a source of competitive advantage for firms. Technology enables firms to collect, interpret, and act on these signals to better manage the customer journey. While some consumers' desire for privacy can restrict the opportunities technology provides marketers, other consumers' desire for personalization can encourage the use of technology to inform marketing efforts. We posit that this difference in consumers' willingness to emit observable signals may hinge on the strength of their relationship with the firm. We next discuss factors that may shift consumer preferences and consequently affect the technology-enabled opportunities available to firms. We conclude with a research agenda that focuses on consumers, firms, and regulators., Author(s): David A. Schweidel [sup.1] , Yakov Bart [sup.2] , J. Jeffrey Inman [sup.3] , Andrew T. Stephen [sup.4] , Barak Libai [sup.5] , Michelle Andrews [sup.1] , Ana Babic [...]

Social media allows people to freely interact with others and offers multiple ways for marketers to reach and engage with consumers. Considering the numerous ways social media affects individuals and businesses alike, in this article, the authors focus on where they believe the future of social media lies when considering marketing-related topics and issues. Drawing on academic research, discussions with industry leaders, and popular discourse, the authors identify nine themes, organized by predicted imminence (i.e., the immediate, near, and far futures), that they believe will meaningfully shape the future of social media through three lenses: consumer, industry, and public policy. Within each theme, the authors describe the digital landscape, present and discuss their predictions, and identify relevant future research directions for academics and practitioners., Author(s): Gil Appel [sup.1] , Lauren Grewal [sup.2] , Rhonda Hadi [sup.3] , Andrew T. Stephen [sup.3] [sup.4] Author Affiliations: (1) grid.42505.36, 0000 0001 2156 6853, Marshall School of Business, [...]

Marketing scholars increasingly use web scraping and application programming interfaces (APIs) to collect data from the internet. Yet, despite the widespread use of such web data, the idiosyncratic and sometimes insidious challenges in its collection have received limited attention. How can researchers ensure that the data sets generated via web scraping and APIs are valid? While existing resources emphasize technical details of extracting web data, the authors propose a novel methodological framework focused on enhancing its validity. In particular, the framework highlights how addressing validity concerns requires the joint consideration of idiosyncratic technical and legal/ethical questions along the three stages of collecting web data: selecting data sources, designing the data collection, and extracting the data. The authors further review more than 300 articles using web data published in the top five marketing journals and offer a typology of how web data have advanced marketing thought. The article concludes with directions for future research to identify promising web data sources and embrace novel approaches for using web data to capture and describe evolving marketplace realities. [ABSTRACT FROM AUTHOR]

As mobile phones continue to rapidly expand around the world, marketers are seeking to better understand the impact these devices have on consumer outcomes. One common but understudied area is how mobile phones may influence in-store behaviors. Although prior research has investigated the many shopping related activities consumers undertake on their phones, it is still estimated that nearly half of all in-store mobile phone use is unrelated to the shopping task. Therefore, this paper examines the impact of shopping-unrelated mobile phone use, a frequent but understudied phenomenon, on consumers' ability to accurately manage in-store shopping plans. Using both field and experimental data, we demonstrate that shopping-unrelated mobile phone use negatively affects consumers' ability to accurately carry out in-store shopping plans and is associated with an increase in unplanned purchasing. Furthermore, we find that consumers who are highly dependent upon mobile phones tend to be the most at risk of deviating from a shopping plan while engaging in shopping-unrelated mobile phone use., Author(s): Michael R. Sciandra [sup.1] , J. Jeffrey Inman [sup.2] , Andrew T. Stephen [sup.3] Author Affiliations: (Aff1) 0000 0001 0727 1047, grid.255794.8, Dolan School of Business, Fairfield University, , [...]

Chatbots have become common in digital customer service contexts across many industries. While many companies choose to humanize their customer service chatbots (e.g., giving them names and avatars), little is known about how anthropomorphism influences customer responses to chatbots in service settings. Across five studies, including an analysis of a large real-world data set from an international telecommunications company and four experiments, the authors find that when customers enter a chatbot-led service interaction in an angry emotional state, chatbot anthropomorphism has a negative effect on customer satisfaction, overall firm evaluation, and subsequent purchase intentions. However, this is not the case for customers in nonangry emotional states. The authors uncover the underlying mechanism driving this negative effect (expectancy violations caused by inflated pre-encounter expectations of chatbot efficacy) and offer practical implications for managers. These findings suggest that it is important to both carefully design chatbots and consider the emotional context in which they are used, particularly in customer service interactions that involve resolving problems or handling complaints. [ABSTRACT FROM AUTHOR]

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.

How can we know what stakeholders think and feel about brands in real time and over time? Most brand reputation measures are at the aggregate level (e.g., the Interbrand "Best Global Brands" list) or rely on customer brand perception surveys on a periodical basis (e.g., the Y&R Brand Asset Valuator). To answer this question, brand reputation measures must capture the voice of the stakeholders (not just ratings on brand attributes), reflect important brand events in real time, and connect to a brand's financial value to the firm. This article develops a new social media–based brand reputation tracker by mining Twitter comments for the world's top 100 brands using Rust–Zeithaml–Lemon's value–brand–relationship framework, on a weekly, monthly, and quarterly basis. The article demonstrates that brand reputation can be monitored in real time and longitudinally, managed by leveraging the reciprocal and virtuous relationships between the drivers, and connected to firm financial performance. The resulting measures are housed in an online longitudinal database and may be accessed by brand reputation researchers. [ABSTRACT FROM AUTHOR]

The article offers information about manuscript review process by relevance, what makes some papers more publication-worthy than others, by using words like interesting, novel, insightful, useful, impactful, or important.

The editors note aspects of the publication of the "Journal of Consumer Research" that they are focusing on, in light of their new appointment as periodical editors, which includes timely publication of topics and the peer review process; organizational transparency; and their policies of diversity, equity, and inclusion.