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A pricing model for group buying based on network effects

Group buying (GB) is a popular business model in e-commerce. With the rise of online social media, the positive network effect of buying with others is more important than price discount for consumers to choose GB. However, the negative network effect of GB is also significant for some consumers. In...

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Detalles Bibliográficos
Autor principal: Ni, Guanqun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6345429/
https://www.ncbi.nlm.nih.gov/pubmed/30677089
http://dx.doi.org/10.1371/journal.pone.0211109
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author Ni, Guanqun
author_facet Ni, Guanqun
author_sort Ni, Guanqun
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description Group buying (GB) is a popular business model in e-commerce. With the rise of online social media, the positive network effect of buying with others is more important than price discount for consumers to choose GB. However, the negative network effect of GB is also significant for some consumers. In this paper, we classify consumers into two segments considering both positive and negative network effects, and three possible sales strategies as well as their optimal decisions on price are presented. We find that GB strategy dominates individual buying (IB) strategy when the positive network effect is sufficiently high or the proportion of consumers with low valuation is relatively large. We also find that MIX strategy offering both IB and GB is always better than IB, while the relationship between MIX and GB is depending on actual market situations. Some other managerial insights are also discussed.
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spelling pubmed-63454292019-02-02 A pricing model for group buying based on network effects Ni, Guanqun PLoS One Research Article Group buying (GB) is a popular business model in e-commerce. With the rise of online social media, the positive network effect of buying with others is more important than price discount for consumers to choose GB. However, the negative network effect of GB is also significant for some consumers. In this paper, we classify consumers into two segments considering both positive and negative network effects, and three possible sales strategies as well as their optimal decisions on price are presented. We find that GB strategy dominates individual buying (IB) strategy when the positive network effect is sufficiently high or the proportion of consumers with low valuation is relatively large. We also find that MIX strategy offering both IB and GB is always better than IB, while the relationship between MIX and GB is depending on actual market situations. Some other managerial insights are also discussed. Public Library of Science 2019-01-24 /pmc/articles/PMC6345429/ /pubmed/30677089 http://dx.doi.org/10.1371/journal.pone.0211109 Text en © 2019 Guanqun Ni http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Ni, Guanqun
A pricing model for group buying based on network effects
title A pricing model for group buying based on network effects
title_full A pricing model for group buying based on network effects
title_fullStr A pricing model for group buying based on network effects
title_full_unstemmed A pricing model for group buying based on network effects
title_short A pricing model for group buying based on network effects
title_sort pricing model for group buying based on network effects
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6345429/
https://www.ncbi.nlm.nih.gov/pubmed/30677089
http://dx.doi.org/10.1371/journal.pone.0211109
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