The Value of Subjective and Objective High-Frequency Service Quality Data: An Empirical Analysis
44 Pages Posted: 16 Jul 2015 Last revised: 11 May 2021
Date Written: May 1, 2021
The advent of digitization has allowed firms to collect high-frequency data - subjective and objective - to monitor their service performance. This paper proposes a methodological framework to help firms understand the value of collecting these data. We apply the framework to novel high-frequency, individual-level, cross-sectional and time-series measures of subjective post-purchase perceptions (via surveys) and objective operational metrics from a quick service restaurant and an auto rental company. Our approach allows for the quantification of the statistical and economic significance of collecting high-frequency subjective survey data in the presence of its objective counterpart. In both settings, our results show that not collecting subjective data can lead to economically significant biases in resource allocation. The value of these data is the highest for frequent customers. We also find the presence of both within- and across-individual selection in survey response, with the latter having a much bigger impact on the results. Our findings advance the literature on measurement and management of service performance and provide insights to managers for forecasting and resource allocation in service settings.
Keywords: Service Quality, High-frequency Data, Within-individual Selection, Across-individual Selection, Machine Learning, QSR, Auto Rental
JEL Classification: L1, L8, M3
Suggested Citation: Suggested Citation