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Multidimensional gap analysis

Authors: S. Amato; PALUMBO, FRANCESCO;

Multidimensional gap analysis

Abstract

In many fields of the socio-economic analysis, the really interesting information consist of two parts: the absolute level and the deviation with respect to an “expected” value. Deviations are also called gaps. Dealing with one or few indicators, the gap analysis can be faced with classical statistical methods. However, in the case of complex phenomena (described by many variables) a descriptive multidimensional approach can offer better results. In this framework, the paper presents a multidimensional approach to look at the gap as a whole concept. In particular, the attention is focused on the Customer Satisfaction analysis, where gaps are defined by the perceived and the expected satisfaction levels and are coded as interval-valued variables. The paper proposes a distance measure between intervals and a suitable factorial treatment to analyze and visualize the gaps over factorial planes.

Country
Italy
Related Organizations
Keywords

Tucker Analysis, Gap Analysis, Interval Data, Gap Analysis; Interval Data; Tucker Analysis

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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