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Location-based pricing and channel selection in a supply chain: a case study from the food retail industry

  • Chen Wei
  • Sobhan AsianEmail author
  • Gurdal Ertek
  • Zhi-Hua Hu
S.I.: RealCaseOR

Abstract

Many retailers nowadays operate in an Internet-enabled dual-channel supply chain setting, referred to as “click and mortar”. In such a structure, products and services are delivered through both online B2C (business-to-consumer e-tail) and offline B2C (traditional brick and mortar retail) channels. In this paper, we develop and present a unified modeling approach that reflects a real-world dual-channel supply chain in the food retail industry. Motivated by the actual business operations of a case study, we incorporate the spatial locations of customers, as well as other logistics and operational costs, into the service provider’s pricing and the customers’ channel choice decisions. We develop two models, namely the benchmark and proposed models, and conduct extensive numerical experiments with parameter values centered on actual values. The results reveal that the ratio of online and offline profit to the total dual-channel profit vary significantly, depending on the locations of customers and the values of the logistics costs. In addition, our statistical and visual analysis suggest that by jointly optimizing the logistics and operational processes, the service provider can achieve a considerably high profit through both channels, without necessarily expanding the size of its geographical service areas.

Keywords

Location-based pricing Channel selection Dual-channel supply chains Food retail industry E-commerce logistics 

Notes

Acknowledgements

We sincerely thank the guest editors and anonymous reviewers for their valuable suggestions and comments. We thank the founding manager of Roza’s Kitchen for initiating the joint industry project and providing information, data, and continuous support throughout the study. This research was supported by the National Natural Science Foundation of China (71471109), the Doctoral Innovation Foundation of Shanghai Maritime University (No. 2017ycx074), and the Shanghai Science and Technology Commission (16040501800). This research was also supported by a Social Research Platform Grant from La Trobe University.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Logistics Research CenterShanghai Maritime UniversityShanghaiChina
  2. 2.La Trobe Business SchoolLa Trobe UniversityMelbourneAustralia
  3. 3.College of BusinessAbu Dhabi UniversityAbu DhabiUAE

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