Accounting for dynamics in attribute-importance and for competitor performance to enhance reliability of BPNN-based importance-performance analysis (CROSBI ID 175551)
Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Mikulić, Josip ; Prebežac, Darko
engleski
Accounting for dynamics in attribute-importance and for competitor performance to enhance reliability of BPNN-based importance-performance analysis
Importance-performance analysis (IPA) is a decision-support tool used in prioritizing quality improvements of products/services. Recently, back- propagation neural network (BPNN)-based approaches have been proposed to deal with the problem of asymmetric effects in customer satisfaction formation. Though reliability of IPA is increased by the integration of BPNN, shortcomings of the analytical framework remain that a) it does not provide insight into forms and degrees of these asymmetric effects, b) it does not account for differences between the relevance and determinance of quality attributes, and c) it neglects the competitor dimension in attribute-prioritization. Since all these issues have important managerial implications, the authors of this study propose an extended BPNN-based IPA that uses a multidimensional operationalization of attribute- importance, and that considers competitive performance levels. Using data from an airline satisfaction survey, an empirical test reveals that the proposed approach significantly outperforms conventional BPNN-based IPA. In particular, conventional BPNN-IPA would mislead managerial action with regard to 3 out of 8 quality components (37.5%).
back-propagation neural network; IPA; relevance; determinance; asymmetric effects
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Podaci o izdanju
39 (5)
2012.
5144-5153
objavljeno
0957-4174
10.1016/j.eswa.2011.11.026
Povezanost rada
Ekonomija, Informacijske i komunikacijske znanosti