Knowledge that Transforms

AbstractManufacturers increasingly adopt health symbols, which translate overall product healthiness into a single symbol, to communicate about the overall healthiness of their grocery products. This study examines how the performance implications of adding a front-of-pack health symbol to a product vary across products. We study the sales impact of a government-supported health symbol program in 29 packaged categories, using over four years of scanner data. The results indicate that health symbols are most impactful when they positively disconfirm pre-existing beliefs that a product is not among the healthiest products within the category. More specifically, we find that health symbols are more effective for (i) products with a front-of-pack taste claim, (ii) lower priced products, and (iii) private label products. Furthermore, these results are more pronounced in healthier categories than in unhealthier categories. Our findings imply that health symbols can help overcome lay beliefs among consumers regarding a product’s overall healthiness. As such, adding a health symbol provides easy-to-process information about product healthiness for the consumer and can increase product sales for the manufacturer.

AbstractDigital transformation of the marketing organization forces firms to develop new digital marketing capabilities (DMCs) to remain competitive. However, despite considerable academic and managerial interest, the value relevance of DMCs beyond the value achieved through classic marketing capabilities (CMCs) remains unclear. Similarly, research investigating the interaction effect of DMCs and CMCs is scarce. We address both research gaps by drawing on a mixed-methods approach combining in-depth interviews and a multi-industry, multisource dataset. The results reveal that DMCs significantly contribute to firm profitability beyond the influence of CMCs. Drawing on the contingent view of resource-based theory, we investigate the moderating influence of organizational and environmental contingencies on the interaction effect of DMCs and CMCs. This investigation reveals important tradeoffs that result in actionable managerial implications for realizing the complementarity potential—and preventing the substitutive potential—of a firm’s DMCs and CMCs.

AbstractArtificial Intelligence is poised to transform all facets of marketing. In this study, we examine the link between firms’ focus on AI in their 10-K reports and their gross and net operating efficiency. 10-K reports are a salient source of insight into an array of issues in accounting and finance research, yet remain relatively overlooked in marketing. Drawing upon economic and marketing theory, we develop a guiding framework to show how firms’ AI focus could be related to gross and net operating efficiency. We then use a system of simultaneous equations to empirically test the relationship between AI focus and operating efficiency. Our findings confirm that US-listed firms are in a state of impending transformation with regards to AI. We show how AI focus is associated with improvements in net profitability, net operating efficiency and return on marketing-related investment while reducing adspend and creating jobs.

AbstractArtificial intelligence (AI) continues to transform firm-customer interactions. However, current AI marketing agents are often perceived as cold and uncaring and can be poor substitutes for human-based interactions. Addressing this issue, this article argues that artificial empathy needs to become an important design consideration in the next generation of AI marketing applications. Drawing from research in diverse disciplines, we develop a systematic framework for integrating artificial empathy into AI-enabled marketing interactions. We elaborate on the key components of artificial empathy and how each component can be implemented in AI marketing agents. We further explicate and test how artificial empathy generates value for both customers and firms by bridging the AI-human gap in affective and social customer experience. Recognizing that artificial empathy may not always be desirable or relevant, we identify the requirements for artificial empathy to create value and deduce situations where it is unnecessary and, in some cases, harmful.