Explore the vast range of titles available.

The amount of digital text available for analysis by consumer researchers has risen dramatically. Consumer discussions on the internet, product reviews, and digital archives of news articles and press releases are just a few potential sources for insights about consumer attitudes, interaction, and culture. Drawing from linguistic theory and methods, this article presents an overview of automated text analysis, providing integration of linguistic theory with constructs commonly used in consumer research, guidance for choosing amongst methods, and advice for resolving sampling and statistical issues unique to text analysis. We argue that although automated text analysis cannot be used to study all phenomena, it is a useful tool for examining patterns in text that neither researchers nor consumers can detect unaided. Text analysis can be used to examine psychological and sociological constructs in consumer-produced digital text by enabling discovery or by providing ecological validity.

Research suggests that consumers are averse to relying on algorithms to perform tasks that are typically done by humans, despite the fact that algorithms often perform better. The authors explore when and why this is true in a wide variety of domains. They find that algorithms are trusted and relied on less for tasks that seem subjective (vs. objective) in nature. However, they show that perceived task objectivity is malleable and that increasing a task's perceived objectivity increases trust in and use of algorithms for that task. Consumers mistakenly believe that algorithms lack the abilities required to perform subjective tasks. Increasing algorithms' perceived affective human-likeness is therefore effective at increasing the use of algorithms for subjective tasks. These findings are supported by the results of four online lab studies with over 1,400 participants and two online field studies with over 56,000 participants. The results provide insights into when and why consumers are likely to use algorithms and how marketers can increase their use when they outperform humans.

In this article we study consumption network effects. Does the consumption of our peers affect our own consumption? How large is such effect? What are the economic mechanisms behind it? We use administrative panel data on Danish households to construct a measure of consumption based on tax records on income and assets. We combine tax record data with matched employer–employee data to identify peer groups based on workplace, which gives us a much tighter and credible definition of networks than used in previous literature. We use the non-overlapping network structure of one’s peers group, as well as firm-level shocks, to build valid instruments for peer consumption. We estimate non-negligible and statistically significant network effects, capable of generating sizable multiplier effect at the macro-level. We also investigate what mechanisms generate such effects, distinguishing between intertemporal and intratemporal consumption effects as well as a more traditional risk sharing view.

Digital goods are, in many cases, substantive innovations relative to their physical counterparts. Yet, in five experiments, people ascribed less value to digital than to physical versions of the same good. Research participants paid more for, were willing to pay more for, and were more likely to purchase physical goods than equivalent digital goods, including souvenir photographs, books (fiction and non-fiction), and films. Participants valued physical goods more than digital goods whether their value was elicited in an incentive compatible pay-what-you-want paradigm, with willingness to pay, or with purchase intention. Greater capacity for physical than digital goods to garner an association with the self (i.e., psychological ownership) underlies the greater value ascribed to physical goods. Differences in psychological ownership for physical and digital goods mediated the difference in their value. Experimentally manipulating antecedents and consequents of psychological ownership (i.e., expected ownership, identity relevance, perceived control) bounded this effect, and moderated the mediating role of psychological ownership. The findings show how features of objects influence their capacity to garner psychological ownership before they are acquired, and provide theoretical and practical insights for the marketing, psychology, and economics of digital and physical goods.

Given the increasingly specific ways marketers can target ads, consumers and regulators are demanding ad transparency: disclosure of how consumers’ personal information was used to generate ads. We investigate how and why ad transparency impacts ad effectiveness. Drawing on literature about offline norms of information sharing, we posit that ad transparency backfires when it exposes marketing practices that violate norms about “information flows”—consumers’ beliefs about how their information should move between parties. Study 1 inductively shows that consumers deem information flows acceptable (or not) based on whether their personal information was: 1) obtained within versus outside of the website on which the ad appears, and 2) stated by the consumer versus inferred by the firm (the latter of each pair being less acceptable). Studies 2 and 3 show that revealing unacceptable information flows reduces ad effectiveness, which is driven by increasing consumers’ relative concern for their privacy over desire for the personalization that such targeting affords. Study 4 shows the moderating role of platform trust: when consumers trust a platform, revealing acceptable information flows increases ad effectiveness. Studies 5a and 5b, conducted in the field with a loyalty program website (i.e., a trusted platform), demonstrate this benefit of transparency.

The consumer Internet of Things (IoT) has the potential to revolutionize consumer experience. Because consumers can actively interact with smart objects, the traditional, human-centric conceptualization of consumer experience as consumers’ internal subjective responses to branded objects may not be sufficient to conceptualize consumer experience in the IoT. Smart objects possess their own unique capacities and their own kinds of experiences in interaction with the consumer and each other. A conceptual framework based on assemblage theory and object-oriented ontology details how consumer experience and object experience emerge in the IoT. This conceptualization is anchored in the context of consumer-object assemblages, and defines consumer experience by its emergent properties, capacities, and agentic and communal roles expressed in interaction. Four specific consumer experience assemblages emerge: enabling experiences, comprising agentic self-extension and communal self-expansion, and constraining experiences, comprising agentic self-restriction and communal self-reduction. A parallel conceptualization of the construct of object experience argues that it can be accessed by consumers through object-oriented anthropomorphism, a nonhuman-centric approach to evaluating the expressive roles objects play in interaction. Directions for future research are derived, and consumer researchers are invited to join a dialogue about the important themes underlying our framework.

People increasingly seek out opportunities to escape from a sped-up pace of life by engaging in slow forms of consumption. Drawing from the theory of social acceleration, we explore how consumers can experience and achieve a slowed-down experience of time through consumption. To do so, we ethnographically study the Camino de Santiago pilgrimage in Spain and introduce the concept of consumer deceleration. Consumer deceleration is a perception of a slowed-down temporal experience achieved via a decrease in certain quantities (traveled distance, use of technology, experienced episodes) per unit of time through altering, adopting, or eschewing forms of consumption. Consumers decelerate in three ways: embodied, technological, and episodic. Each is enabled by consumer practices and market characteristics, rules, and norms, and results in time being experienced as passing more slowly and as being an abundant resource. Achieving deceleration is challenging, as it requires resynchronization to a different temporal logic and the ability to manage intrusions from acceleration. Conceptualizing consumer deceleration allows us to enhance our understanding of temporality and consumption, embodied consumption, extraordinary experiences, and the theory of social acceleration. Overall, this study contributes to consumer research by illuminating the role of speed and rhythm in consumer culture.

Itravel Country, like my Old People done. I see the Country, like my Old Peopledone I burn Country, like my Old People done. I sing Country, like my Old Peopledone - JacobMorris, Ban Maganindadjyang (My Old People Done).

Are social media posts with pictures more popular than those without? Why do pictures with certain characteristics induce higher engagement than some other pictures? Using data sets of social media posts about major airlines and sport utility vehicle brands collected from Twitter and Instagram, the authors empirically examine the influence of image content on social media engagement. After accounting for selection bias on the inclusion of image content, the authors find a significant and robust positive mere presence effect of image content on user engagement in both product categories on Twitter. They also find that high-quality and professionally shot pictures consistently lead to higher engagement on both platforms for both product categories. However, the effect of colorfulness varies by product category, while the presence of human face and image–text fit can induce higher user engagement on Twitter but not on Instagram. These findings shed light on how to improve social media engagement using image content.

Consumer-to-consumer brand message sharing is pivotal for effective social media marketing. Even as companies join social media conversations and generate millions of brand messages, it remains unclear what, how, and when brand messages stand out and prompt sharing by consumers. With a conceptual extension of speech act theory, this study offers a granular assessment of brands’ message intentions (i.e., assertive, expressive, or directive) and the effects on consumer sharing. A text mining study of more than two years of Facebook posts and Twitter tweets by well-known consumer brands empirically demonstrates the impacts of distinct message intentions on consumers’ message sharing. Specifically, the use of rhetorical styles (alliteration and repetitions) and cross-message compositions enhance consumer message sharing. As a further extension, an image-based study demonstrates that the presence of visuals, or so-called image acts, increases the ability to account for message sharing. The findings explicate brand message sharing by consumers and thus offer guidance to content managers for developing more effective conversational strategies in social media marketing.