TITLE:
Critique of the Linear-Compensatory Approach in Customer Satisfaction Measurement: An Empirical Study
AUTHORS:
Pushkal Kr. Pandey, Sandra Moffett, Rodney McAdam
KEYWORDS:
Service Quality, Customer Satisfaction Measurement, Linear Regression Model, Information Integration Theory
JOURNAL NAME:
Theoretical Economics Letters,
Vol.9 No.4,
April
30,
2019
ABSTRACT:
Purpose of the Study: The researchers critique
the linear-compensatory combinatorial rule used in the expectancy-value model
that is widely applied to explain how customers integrate attribute-level
information in satisfaction judgements. Data/Methodology: The data have been collected from
customers of an online travel agency. The surveys were administered via email,
after their interaction with customer service advisor on telephone. The survey
instrument is largely based on the SERVQUAL model, with a few additional items
pertaining to the call centre context. A randomly selected sample of 626 usable
responses was obtained based on completeness of data. As compared to the
traditional methods, where a summary analysis of aggregated data is done, the
present data analysis follows a deconstructive approach, involving assessing
changes in degree of satisfaction brought about by change in each degree of
performance for every quality attribute. Findings: By following a unique
analytical approach to analysing survey data, the study classifies customer
satisfaction as not unlike other evaluative judgements, such as morality and
likableness, where summary evaluations are a result of a cumulative assessment
of all attributes that constitute the particular context. Originality: This study explores the process of cognitive appraisal, which underlies the
combination of varied service quality information, in the form of attributes of
service quality into unitary satisfaction judgements.