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

See all articles by Jihoon Cho

Jihoon Cho

Kansas State University - College of Business Administration

Anocha Aribarg

University of Michigan at Ann Arbor - Stephen M. Ross School of Business

Puneet Manchanda

University of Michigan, Stephen M. Ross School of Business

Date Written: May 1, 2021

Abstract

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

Cho, Jihoon and Aribarg, Anocha and Manchanda, Puneet, The Value of Subjective and Objective High-Frequency Service Quality Data: An Empirical Analysis (May 1, 2021). Ross School of Business Paper No. 1283, Available at SSRN: https://ssrn.com/abstract=2630898 or http://dx.doi.org/10.2139/ssrn.2630898

Jihoon Cho (Contact Author)

Kansas State University - College of Business Administration ( email )

Manhattan, KS 66506
United States

Anocha Aribarg

University of Michigan at Ann Arbor - Stephen M. Ross School of Business ( email )

701 Tappan Street
Ann Arbor, MI MI 48109
United States

Puneet Manchanda

University of Michigan, Stephen M. Ross School of Business ( email )

701 Tappan Street
Ann Arbor, MI MI 48109
United States
734-936-2445 (Phone)
734-936-8716 (Fax)

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