Digital Technologies, Customer Experience, and Decisions
Author(s)
Yu, Shuyi
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Advisor
Tucker, Catherine
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This dissertation consists of three chapters that investigate how digital technologies have changed customer experience and their decisions.
The first chapter investigates market participants’ reactions to predictive algorithms and the effects of this public information source on market outcomes. In particular, I study the extent to which buyers and sellers rely on a home’s Zestimate when making decisions. Using detailed property transaction data for 120,482 properties sold between May 2017 and May 2019 in the Greater Philadelphia area, I show that the sale price of a property does respond to exogenous shocks to its estimated home value. I develop a theoretical framework and provide empirical evidence to show how people use the Zestimate as a source of publicly available information that plays an important role in coordination and helping people reach an agreement. The results suggest that market participants tend to rely more on this public information source when it is harder to reach a consensus based on private information. Moreover, I show that people’s reliance on the Zestimate might mitigate racial disparities in the housing market by providing less biased information.
In the second chapter, we study how consumers respond to repeated marketing campaigns driven by algorithms and how the responses vary across different algorithms. To investigate it, we collaborate with a U.S. food delivery company and conduct a field experiment where targeted coupons are sent by applying the same algorithms repeatedly. Our results show that algorithms utilizing more information perform better than simpler algorithms, and this difference only exists when the consumers have already been treated by the same algorithmdriven policy a few times. By exploring the variation in the purchase patterns, we show that those differences arise because advanced algorithms reduce the level of learning and strategic behaviors against the rules. This result also suggests that consumers may have some level of algorithm awareness, especially when algorithms are easy to learn, and are forward-looking enough to play strategically against the policies powered by those algorithms.
In the third chapter, we study how digitization has transformed customer experience in the public sector. Customers with more education may get better service after complaining, because they are better placed to advocate for themselves. It is unclear how digitization of the consumer complaint process will change this situation. To investigate this, we analyze 364,189 customer complaints to the city of Boston. Empirically, complaints that originate 3 from areas with high levels of education are more likely to be solved quickly. However, dedicated mobile app technologies that automate the complaint process can help mitigate the advantage conferred by education. Since the adoption of digital devices is endogenous to wealth and education, we instrument their usage using granular geographic data on a proxy for cellular signal strength. This analysis again suggests that mobile applications can partially eliminate the disparity between educated and uneducated people. We present suggestive evidence that this is because mobile devices and the standardization of communication they require, eliminate potential differences in treatment of cases that arise due to differences in communication skills. This result suggests that using newer forms of automated digital communication tools enhances equality in customer service.
Date issued
2021-06Department
Sloan School of ManagementPublisher
Massachusetts Institute of Technology