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Key-Driver Analysis with Extended Back- Propagation Neural Network Based Importance- Performance Analysis (BPNN-IPA) (CROSBI ID 54898)

Prilog u knjizi | izvorni znanstveni rad

Mikulić, Josip ; Krešić, Damir ; Miličević, Katarina Key-Driver Analysis with Extended Back- Propagation Neural Network Based Importance- Performance Analysis (BPNN-IPA) // Intelligent Decision Making in Quality Management - Theory and Applications / Kahraman, Cengiz ; Yanık, Seda (ur.). Cham: Springer, 2016. str. 447-461

Podaci o odgovornosti

Mikulić, Josip ; Krešić, Damir ; Miličević, Katarina

engleski

Key-Driver Analysis with Extended Back- Propagation Neural Network Based Importance- Performance Analysis (BPNN-IPA)

Importance-performance analysis (IPA) is a popular prioritization tool used to formulate effective and efficient quality improvement strategies for products and services. Since its introduction in 1977, IPA has undergone numerous enhancements and extensions, mostly with regard to the operationalization of attribute-importance. Recently, studies have promoted neural network -based IPA approaches to determine attribute-importance more reliably compared to traditional approaches. This chapter describes the application of back- propagation neural networks (BPNN) in an extended IPA framework with the goal of discovering key areas of quality improvements. The value of the extended BPNN-based IPA is demonstrated using an empirical case example of airport service quality .

Back-propagation, Neural network, Importance-performance analysis, Attribute importance, Service quality

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Podaci o prilogu

447-461.

objavljeno

Podaci o knjizi

Kahraman, Cengiz ; Yanık, Seda

Cham: Springer

2016.

978-3-319-24497-6

Povezanost rada

Ekonomija