Programmatic advertising in online retailing: Consumer perceptions and future avenues

Robert Ciuchita, Johanna Gummerus, Maria Holmlund*, Eva Larissa Linhart

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Purpose: Digital advertising enables retailers to rely on large volumes of data on consumers and even leverage artificial intelligence (AI) to target consumers online with personalised and context-aware advertisements. One recent example of such advertisements is programmatic advertising (PA), which is facilitated by automatic bidding systems. Given that retailers are expected to increase their use of PA in the future, further insights on the pros and cons of PA are required. This paper aims to enhance the understanding of the implications of PA use for retailers.
Design/methodology/approach: A theoretical overview is conducted that compares PA to traditional advertising, with an empirical investigation into consumer attitudes towards PA (an online survey of 189 consumers using an experimental design) and a research agenda.
Findings: Consumer attitudes towards PA are positively related to attitudes towards the retailer. Further, perceived ad relevance is positively related to attitudes towards PA, which is moderated by (1) consumer perceptions of risks related to sharing their data with retailers online and (2) consumer perceptions of AI's positive potential. Surprisingly, the disclosed use of AI for PA does not significantly influence consumer attitudes towards PA.
Originality/value: This paper contributes to the literature on technology-enabled services by empirically demonstrating that ad relevance drives consumer attitudes towards PA. This paper further examines two contingencies: risk beliefs related to data (i.e. the source of PA) and perceptions of AI (i.e. the somewhat nebulous technology associated with PA) as beneficial. A research agenda illuminates central topics to guide future research on PA in retailing.

Original languageEnglish
Peer-reviewed scientific journalJournal of Service Management
ISSN1757-5818
DOIs
Publication statusPublished - 22.06.2022
MoE publication typeA1 Journal article - refereed

Keywords

  • 512 Business and Management
  • programmatic advertising
  • online retailing
  • risk beliefs
  • ad relevance
  • artificial intelligence
  • smart PLS

Areas of Strength and Areas of High Potential (AoS and AoHP)

  • AoS: Competition economics and service strategy - Service and customer-oriented management

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