Knowledge that Transforms

Influencer marketing initiatives require firms to select and incentivize online influencers to engage their followers on social media in an attempt to promote the firms’ offerings. However, limited research considers the costs of influencer marketing when evaluating these campaigns’ effectiveness, particularly from an engagement elasticity perspective. Moreover, it is unclear whether and how marketers could enhance influencer marketing effectiveness by strategically selecting influencers, targeting their followers, or managing content. This study draws on a communication model to examine how factors related to the sender of a message (influencer), the receiver of the message (influencer's followers), and the message itself (influencer's posts) determine influencer marketing effectiveness. The findings show that influencer originality, follower size, and sponsor salience enhance effectiveness, and posts that announce new product launches diminish it. Several tensions arise when firms select influencers and manage content: Influencer activity, follower–brand fit, and post positivity all exert inverted U-shaped moderating effects on influencer marketing effectiveness, suggesting that firms that adopt a balanced approach along these dimensions can achieve greater effectiveness. These novel insights offer important implications for marketers designing influencer marketing campaigns.

Social norms shape consumer behavior. However, it is not clear under what circumstances social norms are more versus less effective in doing so. This gap is addressed through an interdisciplinary meta-analysis examining the impact of social norms on consumer behavior across a wide array of contexts involving the purchase, consumption, use, and disposal of products and services, including socially approved (e.g., fruit consumption, donations) and disapproved (e.g., smoking, gambling) behaviors. Drawing from reactance theory and based on a cross-disciplinary data set of 250 effect sizes from research spanning 1978–2019 representing 112,478 respondents from 22 countries, the authors examine the effects of five categories of moderators of the effectiveness of social norms on consumer behavior: (1) target behavior characteristics, (2) communication factors, (3) consumer costs, (4) environmental factors, and (5) methodological characteristics. The findings suggest that while the effect of social norms on approved behavior is stable across time and cultures, their effect on disapproved behavior has grown over time and is stronger in survival and traditional cultures. Communications identifying specific organizations or close group members enhance compliance with social norms, as does the presence of monetary costs. The authors leverage their findings to offer managerial implications and a future research agenda for the field.

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.

A core assumption across many disciplines is that producers enter market exchange relationships for economic reasons. This research examines an overlooked factor; namely, the socioemotional benefits of selling the fruits of one's labor. Specifically, the authors find that individuals selling their products interpret sales as a signal from the market that serves as a source of self-validation, thus increasing their happiness above and beyond any monetary rewards from those sales. This effect highlights an information asymmetry that is opposite to what is found in traditional signaling theory. That is, the authors find that customers have information about product quality that they signal to the producer, validating the producer's skill level. Furthermore, the sales-as-signal effect is moderated by characteristics of the purchase transaction that determine the signal strength of sales: The effect is attenuated when product choice does not reflect a deliberate decision and is amplified when buyers incur higher monetary costs. In addition, sales have a stronger effect on happiness than alternative, nonmonetary forms of market signals such as likes. Finally, the sales-as-signal effect is more pronounced when individuals sell their self-made (vs. other-made) products and affects individuals’ happiness beyond the happiness gained from producing.

Sharing economy platforms have become increasingly popular, but many platforms do not create all the value that is possible because consumers face challenges while cocreating their experiences. The authors situate the origin of these challenges in the sharing economy’s hybrid cocreation logics, which combine competing communal and transactional logics. Using a qualitative study of Couchsurfing, a platform for sharing free accommodation, the authors find that consumers engage in orchestration work to overcome cocreation roadblocks and extract greater benefits from sharing economy platforms. This orchestration work consists of many actions reflected in four overarching mechanisms: consumer-to-consumer alignment, rewiring relations, trust investment, and network experimentation. The authors connect these mechanisms to known sources of value for firms (i.e., complementarities, efficiency, lock-in, and novelty) to make recommendations for how platform firms can foster consumer orchestration work and unlock the full value of consumer cocreation in the sharing economy.

Digital platforms that aggregate products and services, such as Google Shopping or Amazon, have emerged as powerful intermediaries to brand offerings, challenging traditional product brands that have largely lost direct access to consumers. As a countermeasure, several long-established brands have built their own flagship platforms to resume control and foster consumer loyalty. For example, sports brands such as Nike, Adidas, or Asics launched tracking and training platforms that allow for ongoing versatile interactions among participants beyond product purchase. The authors analyze these emerging platform offerings, whose potential brands struggle to exploit, and provide guidance for brands that aim to platformize their business. This guidance comprises the conceptualization of digital platforms as places of consumer crowdsourcing (i.e., consumers drawing value from platform participants such as the brand, other consumers, or third-party businesses) and crowdsending (i.e., consumers providing value to platform participants) of products, services, and content along with a well-defined framework that brands can apply to assemble different types of flagship platforms. Evaluating the consequences of crowdsourcing and crowdsending for consumer–platform relationships, the authors derive a typology of archetypical relationship states and develop a set of propositions to help offline-born product brands thrive through platformization.

The proliferating gig economy relies on online freelance marketplaces, which support relatively anonymous interactions through text-based messages. Informational asymmetries thus arise that can lead to exchange uncertainties between buyers and freelancers. Conventional marketing thought recommends reducing such uncertainty. However, uncertainty reduction and uncertainty management theories indicate that buyers and freelancers might benefit more from balancing—rather than reducing—uncertainty, such as by strategically adhering to or deviating from common communication principles. With dyadic analyses of calls for bids and bids from a leading online freelance marketplace, this study reveals that buyers attract more bids from freelancers when they provide moderate degrees of task information and concreteness, avoid sharing personal information, and limit the affective intensity of their communication. Freelancers’ bid success and price premiums increase when they mimic the degree of task information and affective intensity exhibited by buyers. However, mimicking a lack of personal information and concreteness reduces freelancers’ success, so freelancers should always be more concrete and offer more personal information than buyers. These contingent perspectives offer insights into buyer–seller communication in two-sided online marketplaces. They clarify that despite, or sometimes due to, communication uncertainty, both sides can achieve success in the online gig economy.

Consumption can provide a feeling of groundedness or being emotionally rooted. This can occur when products connect consumers to their physical (place), social (people), and historic (past) environment. The authors introduce the concept of groundedness to the literature and show that it increases consumer choice; happiness; and feelings of safety, strength, and stability. Following these consequential outcomes, the authors demonstrate how marketers can provide consumers with a feeling of groundedness through product designs, distribution channels, and marketing communications. They also show how marketers might segment the market using observable proxies for consumers’ need for groundedness, such as high computer use, high socioeconomic status, or life changes brought on by the COVID-19 pandemic. Taken together, the findings show that groundedness is a powerful concept providing a comprehensive explanation for a variety of consumer trends, including the popularity of local, artisanal, and nostalgic products. It seems that in times of digitization, urbanization, and global challenges, the need to feel grounded has become particularly acute.

Firms increasingly follow an “always on” philosophy, publishing multiple pieces of firm-generated content (FGC) every day. Current methodologies used in marketing are unfit to unbiasedly capture the impact of FGC disseminated intermittently throughout the day on stock markets characterized by ultra-high-frequency trading. They also neither distinguish between the permanent (i.e., long-term) and temporary (i.e., short-term) price impacts nor identify FGC attributes capable of generating these price impacts. In this study, the authors define price impact as the impact on the variance of stock price. Employing a market microstructure approach to exploit the variance of high-frequency changes in stock price, the authors estimate the permanent and temporary price impacts of the firm-generated Twitter content of S&P 500 information technology firms. The authors find that firm-generated tweets induce both permanent and temporary price impacts, which are linked to tweet attributes of valence and subject matter. Tweets reflecting only valence or subject matter concerning consumer or competitor orientation result in temporary price impacts, whereas those embodying both attributes generate permanent price impacts. Negative-valence tweets about competitors generate the largest permanent price impacts. Building on these findings, the authors offer suggestions to marketing managers regarding the design of intraday FGC.

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.