In recent years, many new and interesting models of successful online business have been developed, including competitive models such as auctions, where the product price tends to rise, and group-buying, where users cooperate obtaining a dynamic price that tends to go down. We propose the e-fair as a business model for social commerce, where both sellers and buyers are grouped to maximize benefits. e-Fairs extend the group-buying model aggregating demand and supply for price optimization as well as consolidating shipments and optimize withdrawals for guaranteeing additional savings. e-Fairs work upon multiple dimensions: time to aggregate buyers, their geographical distribution, price/quantity curves provided by sellers, and location of withdrawal points. We provide an analytical model for time and spatial optimization and simulate realistic scenarios using both real purchase data from an Italian marketplace and simulated ones. Experimental results demonstrate the potentials offered by e-fairs and show benefits for all the involved actors.

Gallo, P., Randazzo, F., Gallo, I. (2017). e-Fair: Aggregation in e-Commerce for Exploiting Economies of Scale [Rapporto tecnico].

e-Fair: Aggregation in e-Commerce for Exploiting Economies of Scale

GALLO, Pierluigi;Randazzo, Francesco;
2017-01-01

Abstract

In recent years, many new and interesting models of successful online business have been developed, including competitive models such as auctions, where the product price tends to rise, and group-buying, where users cooperate obtaining a dynamic price that tends to go down. We propose the e-fair as a business model for social commerce, where both sellers and buyers are grouped to maximize benefits. e-Fairs extend the group-buying model aggregating demand and supply for price optimization as well as consolidating shipments and optimize withdrawals for guaranteeing additional savings. e-Fairs work upon multiple dimensions: time to aggregate buyers, their geographical distribution, price/quantity curves provided by sellers, and location of withdrawal points. We provide an analytical model for time and spatial optimization and simulate realistic scenarios using both real purchase data from an Italian marketplace and simulated ones. Experimental results demonstrate the potentials offered by e-fairs and show benefits for all the involved actors.
Gallo, P., Randazzo, F., Gallo, I. (2017). e-Fair: Aggregation in e-Commerce for Exploiting Economies of Scale [Rapporto tecnico].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/244908
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