ASSORTMENTCUSTOMIZE

Real-time Assortment Customization for Products with Dynamic Content: Theory and an Application to Interactive TV

Coordinatore	ERASMUS UNIVERSITEIT ROTTERDAM    more  Organization address address: BURGEMEESTER OUDLAAN 50 city: ROTTERDAM postcode: 3062 PA contact info Titolo: Mr. Nome: Reino Cognome: De Boer Email: send email Telefono: 31104081346
Nazionalità Coordinatore	Netherlands [NL]
Totale costo	185˙540 €
EC contributo	185˙540 €
Programma	FP7-PEOPLE Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
Code Call	FP7-PEOPLE-2010-IIF
Funding Scheme	MC-IIF
Anno di inizio	2011
Periodo (anno-mese-giorno)	2011-04-01   -   2013-03-31

 Partecipanti

#	participant	country	role	EC contrib. [€]
1	ERASMUS UNIVERSITEIT ROTTERDAM  Organization address address: BURGEMEESTER OUDLAAN 50 city: ROTTERDAM postcode: 3062 PA contact info Titolo: Mr. Nome: Reino Cognome: De Boer Email: send email Telefono: 31104081346	NL (ROTTERDAM)	coordinator	185˙540.80

Mappa

 Word cloud

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 Obiettivo del progetto (Objective)

'In many industries, firms give consumers more choice options than they can choose, in a phenomenon that has been described as the paradox of choice. When products are created and updated very rapidly, the problem is worse e.g., consumers often have hundreds of cable TV programs to choose from. This project proposes a method to optimally customize the assortment of products shown to consumers according to each consumer' s individual characteristics. The method first identifies product category membership for each product, and looks at consumer historical data to infer consumer’s style. Given product categories, consumer style, product price and cost, the method uses dynamic programming to identify the best shortlist of products to be offered to each consumer. Next, the consumer makes a decision (to choose or not a product from the list). The decision is then used to update the optimization algorithm. The method proposed in this project will be tested in one industry in particular (cable TV), but it will be general enough to be applicable to others. The method is based on cutting-edge optimization technology. This knowledge was developed at MIT and published by the applicant along with MIT senior professors in the best journal of the marketing field (Marketing Science). The applicant’s 2009 paper was the finalist of the prestigious John D.C.Little Award, and received Elsevier's Citations of Excellence award. It was published as the leading paper of its issue, with commentaries by leading scholars. The overall research strategy is to develop and solve the model, gather empirical priors from a field survey, run empirically-based simulations to obtain a proof-of-concept, and then empirically test the algorithm in the field. The implementation of the project includes the creation of a lab at the EUR with graduate students. The EUR will give full support including reduced teaching load, computing resources, mentoring, research budget and students.'

Introduzione (Teaser)

Online shopping systems recommend additional products but not in a very helpful manner. A new system intelligently tailors profitable recommendations to the user.