Neural Responses to Hedonic and Utilitarian Banner Ads: An fMRI Study

Though artificial intelligence (AI) recommendation is a hot topic in recent marketing research, previous research has shown a convergent tendency for aversion to AI recommendation. It is imperative to find ways to promote AI usage and reduce consumers’ AI aversion. This study fills this void by exploring the effect of AI (vs. human) recommenders on consumers’ preferences for search versus experience products in the context of e‐commerce. Two studies provide convergent evidence that consumers show less avoidance of algorithms when recommending search products compared to experience products. A behavioral experiment (Study 1, N = 112) validates that consumers are less likely to purchase experience products recommended by AI, while there are no significant differences between AI versus human recommenders when recommending search products. Using event‐related potential (ERP), a further consumer neuroscience study (Study 2, N = 26) shows that consumers have a higher level of cognitive conflict (i.e., a larger magnitude of N2) when AI (vs. human) recommends experience products, while the effect disappears for search products. This paper shows that for search products, marketers can obtain similar evaluations using AI recommenders, which is relatively cheaper and more time‐saving compared with human recommenders. Therefore, our work provides important implications for theory and practice on e‐commerce and marketing communication.

Section: Literature Review and Hypotheses Developmentmentioning

confidence: 99%

The searching artificial intelligence: Consumers show less aversion to algorithm‐recommended search product

Xie

Zhang

et al. 2022

“…Consumers' evaluations of products with different attributes lead to different cognitive patterns (Casado et al, 2022). Compared with experience products, search product information is usually standard and objective (e.g., features, performance, etc.…”

Section: Literature Review and Research Hypothesesmentioning

confidence: 99%

Chatbot or human? The impact of online customer service on consumers' purchase intentions

Chen

Liu

et al. 2023

Artificial intelligence (AI) chatbots and human employees have emerged as the dominant forms of online customer service. However, existing research rarely connects the service differences between them in terms of product type, ignoring the interactivity between the two. This study reveals the effect of matching customer service type (AI chatbot vs. human) to product type (search vs. experience) on consumers' purchase intentions through four experiments, revealing the psychological mechanism and boundary condition for the existence of this effect. It shows that (1) the match between customer service type and product type positively affects consumers' purchase intentions; (2) this matching effect is mediated by processing fluency and perceived service quality; and (3) the matching effect works only when consumers' demand certainty is low. These findings enrich the theoretical study of online customer service, and provide marketing insights for companies to improve the adoption of AI chatbots and human employees.

“…These conventional methods have been shown to be accessible, easy to use and cost‐effective in measuring consumer attitudes, intentions, and thoughts (Harris et al, 2018). Nevertheless, self‐reports may be subject to social desirability, useless in evaluating sensitive topics (e.g., sexual or political orientations) or not be able to assess continuous consumer reactions during message exposure (Casado‐Aranda, Sánchez‐Fernández, et al, 2022). Indeed, it may be that attitudes, intentions, or self‐reported ad persuasion do not fully explain audience behavioral changes resulting from a communication campaign, as there may be additional lower‐order cognitive and affective mechanisms in play during message exposure, which may be decisive when it comes to ad outcomes (Weber et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

The application of neuromarketing tools in communication research: A comprehensive review of trends

Casado‐Aranda

Sánchez‐Fernández

Bigné

et al. 2023

This study provides an overview of the evolution of the body of knowledge, current research streams, potential new domains, and theoretical models of interest for neuromarketing research developed in the field of communication. Neuromarketing is defined here as research applying psychophysiological or neuroscience methods in communication. We particularly implemented a comprehensive analysis of 861 publications using keyword cooccurrence analysis and science mapping tools. The performance analysis shows a strong growth in the number of publications over the last decade, with a slight declining impact in terms of citations after reaching a peak around the turn of the century. Contributions published in journals in business and communication fields (and not psychology or neuroimaging) are those with the largest average citations per year. The evolution diagrams highlight that the use of brain imaging tools to study ad persuasion in virtual environments and social marketing contexts (e.g., health or sustainable communication), as well as the employment of novel metrics (neural synchronization) and deep learning methods to analyze data, constitute fruitful research streams in the application of neuromarketing tools in communication research. These results offer communication scholars an accurate insight on recent scientific research applying neuromarketing that can shape further studies.