Costigliola, Francesco (2017) Nonlinear Approach to PLS Path Modelling: Methodology, Software and Application. [Tesi di dottorato]

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Item Type: Tesi di dottorato
Lingua: English
Title: Nonlinear Approach to PLS Path Modelling: Methodology, Software and Application
Creators:
CreatorsEmail
Costigliola, Francescofcostigliola@gmail.com
Date: 10 April 2017
Number of Pages: 272
Institution: Università degli Studi di Napoli Federico II
Department: Scienze Economiche e Statistiche
Dottorato: Statistica
Ciclo di dottorato: 27
Coordinatore del Corso di dottorato:
nomeemail
Lauro, Carlo Nataleclauro@unina.it
Tutor:
nomeemail
Marino, MarinaUNSPECIFIED
Scepi, GermanaUNSPECIFIED
Date: 10 April 2017
Number of Pages: 272
Uncontrolled Keywords: PLS Path Modelling; Nonlinear PLSPM; Component-Based approach; ECSI; Customer Satisfaction; Energy Supply Market
Settori scientifico-disciplinari del MIUR: Area 13 - Scienze economiche e statistiche > SECS-S/01 - Statistica
Date Deposited: 04 May 2017 13:30
Last Modified: 14 Mar 2018 14:09
URI: http://www.fedoa.unina.it/id/eprint/11735
DOI: 10.6093/UNINA/FEDOA/11735

Abstract

This thesis proposes a flexible nonlinear alternative to the PLSPM algorithm which tackles two main issues identified and motivated throughout this study: (i) the presence of linearity assumptions; and (ii) the path direction's incoherence within the inner model estimation phase. The proposed approach can be seen, when it comes to the inner model, as a data-driven estimation approach. In fact, the algorithm adapts to the form assumed by the inner relationships among composites by means of a piecewise estimation method. As detailed and motivated along this work, another added value is represented by the possibility of defining a non-symmetrical weighting system designed to accommodate a coherent path direction modelling among composites. The customer satisfaction application to the energy supply market shows how using the proposed nonlinear approach to PLSPM allows the definition of a more precise business strategy. The results obtained are very promising and the proposed Nonlinear PLSPM approach achieved two main goals: (i) the relation defined in the theoretical model are free from the linearity assumption; (ii) the results provided set the basis for a more suitable interpretation of the relation between composites, based on the natural patterns present in the data.

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