Optimizing box content in try-before-you-buy business models with heterogeneous customer groups
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.14/41434 |
Resumo: | In online retailing, try-before-you-buy business models are emerging. Customers can order items to be shipped home to try and decide which items to keep or send back to the retailer. Usually, this business model is combined with personalized recommendations. In this thesis, an optimization model for supporting the decision of what to put in a box to achieve maximum profit in a sales period is introduced. Multiple periods are simulated and overall profit is analyzed. Profit is evaluated by summing the optimum identified in each period. The optimization model treats customer groups differently based on their purchasing behaviours. Policies and busi ness rules are varied to understand the effects on overall profit and customer groups. From the results, managerial implications are drawn to follow a customer-centric approach. To maximize profit, customers with high lifetime value should be treated as preferred if market demand is high and no other factors limit shipping decisions. Notable limitations include inventory availability and market demand. In market situations with limitations, higher-valued customers should be served first. Once a certain scale of the customer base is reached, it should also be focused on other customer groups. It is shown that the prediction accuracy of input data is a crucial concern for sufficiently optimizing box content. Further works could improve the chosen approach to better understand the effect of actions taking place in future sales periods. |
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Optimizing box content in try-before-you-buy business models with heterogeneous customer groupsTry-before-you-buyCustomer satisfactionLinear optimizationMixed integer programmingSimulationDomínio/Área Científica::Ciências Sociais::Economia e GestãoIn online retailing, try-before-you-buy business models are emerging. Customers can order items to be shipped home to try and decide which items to keep or send back to the retailer. Usually, this business model is combined with personalized recommendations. In this thesis, an optimization model for supporting the decision of what to put in a box to achieve maximum profit in a sales period is introduced. Multiple periods are simulated and overall profit is analyzed. Profit is evaluated by summing the optimum identified in each period. The optimization model treats customer groups differently based on their purchasing behaviours. Policies and busi ness rules are varied to understand the effects on overall profit and customer groups. From the results, managerial implications are drawn to follow a customer-centric approach. To maximize profit, customers with high lifetime value should be treated as preferred if market demand is high and no other factors limit shipping decisions. Notable limitations include inventory availability and market demand. In market situations with limitations, higher-valued customers should be served first. Once a certain scale of the customer base is reached, it should also be focused on other customer groups. It is shown that the prediction accuracy of input data is a crucial concern for sufficiently optimizing box content. Further works could improve the chosen approach to better understand the effect of actions taking place in future sales periods.Na venda a retalho online, estão a surgir modelos de negócio try-before-you-buy. Os clientes podem encomendar artigos a serem enviados para casa para tentarem decidir que artigos guardar ou enviar de volta para o retalhista. Normalmente, este modelo de negócio é combinado com recomendações personalizadas. Nesta tese, é introduzido um modelo de optimização para apoiar a decisão sobre o que colocar numa caixa para obter o máximo lucro num período de vendas. São simulados vários períodos e o lucro global é analisado. O modelo de optimização trata de forma diferente grupos de clientes com base nos seus comportamentos de compra. As políticas são variadas para compreender os efeitos sobre o lucro global e os grupos de clientes. A partir dos resultados, as implicações de gestão são desenhadas para seguir uma abordagem centrada no cliente. Para maximizar o lucro, os clientes com elevado valor vitalício devem ser tratados como preferidos se a procura do mercado for elevada e nenhum outro factor limitar as decisões de expedição. Em situações de mercado com limitações, os clientes de valor mais elevado devem ser ser servidos em primeiro lugar. Uma vez atingida uma certa escala da base de clientes, esta deve também ser concentrada noutros grupos de clientes. Demonstra-se que a precisão da previsão dos dados de entrada é uma preocupação crucial. Outros trabalhos poderão melhorar a abordagem escolhida para compreender melhor o efeito das acções que têm lugar em períodos de vendas futuras.Gijsbrechts, JorenVeritati - Repositório Institucional da Universidade Católica PortuguesaSenftlechner, Martin2023-06-26T10:55:27Z2023-02-022023-012023-02-02T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10400.14/41434TID:203277597enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-12T17:47:00Zoai:repositorio.ucp.pt:10400.14/41434Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T18:34:07.642402Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Optimizing box content in try-before-you-buy business models with heterogeneous customer groups |
title |
Optimizing box content in try-before-you-buy business models with heterogeneous customer groups |
spellingShingle |
Optimizing box content in try-before-you-buy business models with heterogeneous customer groups Senftlechner, Martin Try-before-you-buy Customer satisfaction Linear optimization Mixed integer programming Simulation Domínio/Área Científica::Ciências Sociais::Economia e Gestão |
title_short |
Optimizing box content in try-before-you-buy business models with heterogeneous customer groups |
title_full |
Optimizing box content in try-before-you-buy business models with heterogeneous customer groups |
title_fullStr |
Optimizing box content in try-before-you-buy business models with heterogeneous customer groups |
title_full_unstemmed |
Optimizing box content in try-before-you-buy business models with heterogeneous customer groups |
title_sort |
Optimizing box content in try-before-you-buy business models with heterogeneous customer groups |
author |
Senftlechner, Martin |
author_facet |
Senftlechner, Martin |
author_role |
author |
dc.contributor.none.fl_str_mv |
Gijsbrechts, Joren Veritati - Repositório Institucional da Universidade Católica Portuguesa |
dc.contributor.author.fl_str_mv |
Senftlechner, Martin |
dc.subject.por.fl_str_mv |
Try-before-you-buy Customer satisfaction Linear optimization Mixed integer programming Simulation Domínio/Área Científica::Ciências Sociais::Economia e Gestão |
topic |
Try-before-you-buy Customer satisfaction Linear optimization Mixed integer programming Simulation Domínio/Área Científica::Ciências Sociais::Economia e Gestão |
description |
In online retailing, try-before-you-buy business models are emerging. Customers can order items to be shipped home to try and decide which items to keep or send back to the retailer. Usually, this business model is combined with personalized recommendations. In this thesis, an optimization model for supporting the decision of what to put in a box to achieve maximum profit in a sales period is introduced. Multiple periods are simulated and overall profit is analyzed. Profit is evaluated by summing the optimum identified in each period. The optimization model treats customer groups differently based on their purchasing behaviours. Policies and busi ness rules are varied to understand the effects on overall profit and customer groups. From the results, managerial implications are drawn to follow a customer-centric approach. To maximize profit, customers with high lifetime value should be treated as preferred if market demand is high and no other factors limit shipping decisions. Notable limitations include inventory availability and market demand. In market situations with limitations, higher-valued customers should be served first. Once a certain scale of the customer base is reached, it should also be focused on other customer groups. It is shown that the prediction accuracy of input data is a crucial concern for sufficiently optimizing box content. Further works could improve the chosen approach to better understand the effect of actions taking place in future sales periods. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-06-26T10:55:27Z 2023-02-02 2023-01 2023-02-02T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.14/41434 TID:203277597 |
url |
http://hdl.handle.net/10400.14/41434 |
identifier_str_mv |
TID:203277597 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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