Understanding and predicting demand through visual characteristics and neural networks

Daniela Mast

In order to understand consumers' fashion purchase decisions better, I determine a product's design typicality and brand prominence based on the theories of processing fluency and conspicuous consumption. Then, I relate these visual characteristics to typical product sales patterns to understand how product appearance and sales patterns are related.

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Year of publication:	2023
Authors:	Mast, Daniela
Institutions:	Eberhard Karls Universität Tübingen (degree granting) ; Verlag Dr. Kovač (publisher)
Publisher:	Hamburg : Verlag Dr. Kovac
Subject:	Absatz \| Sales \| Kundenservice \| Customer service \| Online-Handel \| Online retailing \| Textilhandel \| Textile distribution \| Prognoseverfahren \| Forecasting model \| Neuronale Netze \| Neural networks \| Deutschland \| Germany \| Bekleidungshandel \| Electronic Shopping \| Produktgestaltung \| Kaufentscheidung \| Retoure \| Neuronales Netz
Description of contents:	Table of Contents [gbv.de] ; Description [verlagdrkovac.de] ; Description [swbplus.bsz-bw.de]

Extent:	XV, 141 Seiten Illustrationen 21 cm x 14.8 cm, 217 g
Series:	Schriftenreihe electronic commerce, marketing & finance. - Hamburg : Verlag Dr. Kovač, ISSN 2193-7036, ZDB-ID 2661191-0. - Vol. Band 10
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Hochschulschrift
Language:	English
Thesis:	Dissertation, Eberhard Karls Universität Tübingen, 2022
ISBN:	978-3-339-13460-8 ; 3-339-13460-X
Classification:	Marketing
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://ebvufind01.dmz1.zbw.eu/10013534180