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Since the retailing business is a highly competitive industry, the management
team has to monitor the shift of customers needs and their
perception of quality
closely. The awareness of this kind of shift is helpful in adjusting the
management style for each retail store, or even the whole industry.
The key point is the necessity for the management team to grasp the real needs
of customers, and then develop as well as provide the right
service or products .
Therefore, how to discover the real expectation of customers and establish a
measuring mechanism are important issues for researchers.
Due to the inadequacy or inappropriateness in using Likert''s scale method with
traditional way to measure service quality in some industry, this research is
intended to find out a new mechanism for exploring more information when we
have survey data on hand.
We adopt concepts from Fuzzy theory, as well as develop a new two- factor
evaluation schema to serve this purpose. In the scenario of general retailing
business, we modify the retail service quality scale designed by Dabholkar,
Thorpe and Rentz, use it as a vehicle to help the data collection.
Totally, we survey 4 types of 29 retail stores in Taichung
district, obtain 1376
valid questionnaire samples, and then make a comparison between the new "two
factor fuzzy method" against the traditional data treatment by Likert''s scale.
Our major findings are : (1) the performance and importance of data of service
attributes surely show a negatively skew phenomena, and fuzzy multi-criteria
may adjust it back to be normally distributed; (2) what the
customers care most on the
importance of service attributes are all core items, there are no exceptional
expectation from ordinary customers; (3) it is obvious that among 4 types of
etail stores there exists significant difference in the
importance rating of some
service quality dimensions; (4)the two-factor multi-criteria
method shows better
interpretation on the surveyed raw data than the traditional
one, this also means
that two-factor method has potential to discriminate the service quality among
different stores better.
Since all the data collected with retail service quality scale
are ordinal data in
nature, we use the Wilcoxon "Signed Rank Sum Test" and the Kruskal-Wallis
H-Test to perform all the necessary statistical analysis.
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