Research
Research
Did Early ChatGPT-4 Adopters Change Payments to Other Digital Services? Exploratory Evidence from a Consumer Spending Panel
Kim, Seung Hyun, Daniel McCarthy, Kenneth C. Wilbur
Management wisdom dictates that customers "hire" products and services to do "jobs." Does generative artificial intelligence threaten other digital services' "jobs"? We investigate consumer spending data to understand how early ChatGPT-4 subscribers changed their spending on other digital services. We employ Coarsened Exact Matching to balance early adopters with later adopters based on pre-ChatGPT-4 payment data. Then we use a triple-difference identification strategy to predict adopters' counterfactual payments to other digital services. We find two main patterns. First, early ChatGPT-4 adopters tended to also pay for other artificial intelligence services. Second, the estimates rule out market share declines larger than 2% for nearly all other digital service brands and categories. We interpret these non-findings as null effects, providing early evidence that initial generative artificial intelligence technologies did not seriously undermine other digital services' commercial potential.
Gratuities in a Digital Services Marketplace
Kim, Seung Hyun, On Amir, Kenneth C. Wilbur
This paper investigates the psychology underlying tipping behaviors in the online gig economy, providing insights into how digital platforms can encourage tipping, which has the potential to increase overall welfare. Using field data and field experiments, we examine the factors driving online tipping behavior: The results implicate tipping requests implying social norms as primary drivers, as opposed to reciprocity appeals, or strategic tipping behavior. Using a series of lab studies, we further test what aspects of normative messages are particularly impactful and find that providing specific reference levels (i.e., detailed descriptive norms) increases tipping intentions further. This paper highlights marketers’ key role in shaping online tipping behavior and provides initial understanding and guidelines for approaching this task.
Designing Distributed Ledger Technologies, Like Blockchain, for Advertising Markets
Mingyu Joo, Seung Hyun Kim, Anindya Ghose, Kenneth C. Wilbur
Published at IJRM (2023) Link
Distributed Ledger Technologies (DLTs), like Blockchain, could help improve brand safety, consumer privacy and transparency in digital advertising. However, paid advertisements transfer attention, money, and data between three parties: advertiser, consumer, and publisher. Therefore advertising-focused DLTs face more complex design considerations than currency-focused DLTs. We describe four key DLT characteristics: structure, participation/governance, transparency, and terms of exchange. We survey current advertising-focused DLTs and find they each serve only two of the three contracting parties in advertising transactions. We make design recommendations for future advertising-focused DLTs, including a goal of serving both consumers and publishers in addition to advertisers. We also recommend governance, transparency and terms-of-trade considerations. Advertising-focused DLTs have significant promise but also significant obstacles, including multi-sided “chicken-and-egg” problems in standards adoption.