The purpose of this paper is to present the improvement gap analysis (IGA), a simple method to direct improvement opportunities in services that overcomes limitations of the traditional IPA regarding excitement and basic attributes.
The proposed method is theoretically developed and simulated. The theoretical simulation explains why IGA overcomes limitations of the traditional importance performance analysis (IPA) and how it could identify the impact of excitement innovative attributes. A case study with 287 customers of supermarkets was used to empirically test IGA and compare it to IPA.
The case study confirmed that the traditional IPA may lead to wrong improvement decisions for basic and excitement attributes. It happens because IPA is based on current attributes' performance and considers the relationship between attribute performance and customer satisfaction as a linear one. Also, it cannot identify the impact of excitement innovative attributes on customer satisfaction. Using only information about the company's customers, IGA could differentiate neutral from excitement attributes in the case study and, differently from IPA, it correctly identified improvement decisions for basic and excitement attributes.
Although IGA can theoretically distinguish between excitement innovative and neutral attributes, the case study presented in the paper did not test any innovative attribute. All attributes were already experimented or known by the subjects. Future research should empirically test IGA's real capability to identify excitement innovative attributes.
Managers should be aware that IPA may lead to wrong improvement decisions. It may leave excitement attributes unnoticed or direct the company to the improvement of basic attributes that already have adequate performance. IGA can be a good substitute for IPA with the additional advantage that it does not need information about competitors in the analysis. Also, since service quality evaluation depends heavily on customer perception, IGA is particularly suitable to this industry, but it could also be used for product improvement.
The literature presents several papers discussing IPA's problems. Some papers present the possible decision errors of IPA when dealing with excitement and basic attributes. Fewer have tried to propose methods to overcome these problems. This paper confirms the problems of IPA and presents a simple method that overcomes these limitations, distinguishing between excitement and neutral attributes. Also, because it does not use information about competitors, it can be easily used by companies that have difficulties in gathering such information.
Tontini, G. and Dagostin Picolo, J. (2010), "Improvement gap analysis", Managing Service Quality: An International Journal, Vol. 20 No. 6, pp. 565-584. https://doi.org/10.1108/09604521011092893Download as .RIS
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