Mobile Ad Effectiveness: Hyper-Contextual Targeting with Crowdedness

By Michelle Andrews, Xueming Luo, Zheng Fang, Anindya Ghose. Marketing science (Providence, R.I.), 2016

330 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Marketing, Transportation

View Paper: https://www.semanticscholar.org/paper/a2f534b3bfff22eb8936145f4bf2a1cda4f09cbc

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Citations in the corpus

Integrating Marketing Communications: New Findings, New Lessons, and New Ideas (2016, background): “Given its recent emergence due to the explosion of smartphones, academics are just now beginning to develop concerted research on the topic (e.g., Andrews et al. 2016; Fang, Luo, and Keith 2014; Gupta 2013).”
Device Switching in Online Purchasing: Examining the Strategic Contingencies (2018, background): “Andrews et al. (2016) investigate how crowdedness influences the effect of mobile targeting, while Li et al.”
The Influence of Social Crowding on Brand Attachment (2018, background): “Similarly, in a crowded environment where social avoidance is activated, people may turn to their possessions such as their mobile phones to avoid communicating with people in their immediate surroundings (Andrews et al. 2015).”
Geo-Conquesting: Competitive Locational Targeting of Mobile Promotions (2015, background): “Academic research has only recently begun to show how consumers’ real-time context affects mobile marketing effectiveness; for example, promotional response is higher in crowded transit environments (Andrews et al. 2015).”
Marketing Analytics for Data-Rich Environments (2016, neutral): “Using ﬁ eld experiments, Andrews et al. (2015) show that commuters in crowded subway trains are twice as likely to respond to a mobile offer as commuters in noncrowded subway trains.”
A Thematic Exploration of Digital, Social Media, and Mobile Marketing: Research Evolution from 2000 to 2015 and an Agenda for Future Inquiry (2016, background): “Mobile marketing theory development Andrews et al. (2015); Danaher et al.”
The Role of Big Data and Predictive Analytics in Retailing (2017, background): “For example, in mobile advertisements and couponing, Andrews et al. (2015) use a series of field experiments to study mobile ad effectiveness under "hyper-contextual" situational factors such as 'crowdedness' on subway trains; Luo et al. (2014) study the effects of contexts such as current…”