Online and offline cooperation under buy-online, pick-up-in-store: Pricing and inventory decisions

Chen Fan; Yongmei Liu; Xuehua Yang; Xiaohong Chen; Junhua Hu

doi:10.3934/jimo.2018104

Article Contents

2019, Volume 15, Issue 3: 1455-1472. Doi: 10.3934/jimo.2018104

This issue Previous Article Probabilistic control of Markov jump systems by scenario optimization approach Next Article Risk measure optimization: Perceived risk and overconfidence of structured product investors

Online and offline cooperation under buy-online, pick-up-in-store: Pricing and inventory decisions

School of Business, Central South University, Changsha 410083, China

* Corresponding author: liuyongmeicn@163.com
* Corresponding author: liuyongmeicn@163.com

Received: November 2017

Revised: March 2018

Early access: June 2018

Published: April 2019

This work is supported by the National Natural Science Foundation in China (Grant No. 71271219, 71071164 and 71431006), by Major Program of National Social Science Foundation of China (Grant No. 15ZDB169), and by Innovation-Driven Programme of Central South University (Grant No. 2015CX010).

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Abstract

This study considered the problem of pricing and inventory decision-making where an online retailer and an offline retailer cooperate in a setting where buy-online, pick-up-in-store (BOPS) is implemented. Given the extra revenue generated from additional sales by BOPS customers who purchase additional products at the offline outlet, we considered revenue sharing, service subsidy, and inventory subsidy contracts among the coordinating supply chain partners. Optimization models under centralized and decentralized decision-making structures were established, and the solution was found for the equilibrium states of these optimization models. The results from numerical experiments were examined. We found that (1) the optimal stocking factor had different variation trends with the increase in additional sales under a centralized structure and under the three contracts in decentralized scenarios; (2) the revenue sharing contract was the most effective among the three contracts for coordinating online and offline retailers, and it was optimal for both retailers if the additional sales parameter was relatively low and offline cost share was small; and (3) an inventory subsidy contract had strong operability and steadiness under different product characteristics.

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Mathematics Subject Classification: Primary: 90B05, 90B50; Secondary: 91A40.

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Figure 1. The effect of $\alpha$ on decision variables

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Figure 2. The effect of $\alpha$ and $\theta$ on online profits

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Figure 3. The effect of $\alpha$ and $\theta$ on offline profits

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Figure 4. The effect of $\alpha$ and $\theta$ on offline profits

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