Abstract
We propose an instrumental-variable (IV) approach to estimate the causal effect of service satisfaction on customer loyalty by exploiting a common source of randomness in the assignment of service employees to customers in service queues. Our approach can be applied at no incremental cost by using routine repeated cross-sectional customer survey data collected by firms. The IV approach addresses multiple sources of biases that pose challenges in estimating the causal effect using cross-sectional data: (1) the upward bias from common-methods variance resulting from the joint measurement of service satisfaction and loyalty intent in surveys, (2) the attenuation bias caused by measurement errors in service satisfaction, and (3) the omitted variable bias that may be in either direction. In contrast to the common concern about the upward common-methods bias in estimates using cross-sectional survey data, we find that ordinary-least-squares substantially underestimates the causal effect, suggesting that the downward bias resulting from measurement errors and/or omitted variables is dominant. The underestimation is even more significant with a behavioral measure of loyalty, where there is no common-methods bias. This downward bias leads to significant underestimation of the positive profit impact from improving service satisfaction and can lead to underinvestment by firms in service satisfaction. Finally, we find that the causal effect of service satisfaction on loyalty is greater for more difficult types of services. This paper was accepted by Juanjuan Zhang, marketing.
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