Two-period discount pricing strategies for an e-commerce platform with strategic consumers

Li, Chunfa; Chu, Mingsen; Zhou, Chi; Zhao, Lianxia

doi:10.1016/j.cie.2020.106640

Cited by 44 publications

(17 citation statements)

References 37 publications

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“…They found that strategic consumers may yield more revenue in specific scenarios. Li et al [20] established the two-period models to study a platform's discount pricing strategies with strategic consumers. The results show that the large discount will reduce the total demand under the instant strategy, the fraction of strategic consumers affects the platform's strategy choices, and the existence of strategic consumers will increase the product prices for two periods.…”

Section: Literature Reviewmentioning

confidence: 99%

Dynamic air ticket pricing using reinforcement learning method

Gao

Fang

2022

RAIRO-Oper. Res.

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This paper studies a dynamic air ticket pricing problem in a strategic and myopic passengers’ co-existence market. The strategic or myopic passengers can be further divided into high-valuation and low-valuation groups according to how they evaluate their purchases. The strategic passengers have different strategic levels. When the airline sets a ticket price, every passenger makes his or her purchase decision according to his or her type and the strategic level, or might select “wait” or “leave (the market)”. The paper firstly proposes a dynamic pricing algorithm in which the utilities of both the airline and passengers are considered. The reinforcement learning (RL) is employed to deal with the progressive or dynamic decision-making framework, in which the dynamic pricing problem is formulated as a discrete finite Markov decision process (MDP) and the Q-learning is adopted to solve the problem. By using this method, the airline can adaptively decide the ticket price based on passengers’ strategic behaviors and the time-varying demand. The effects of the passenger type proportion and strategic level are analyzed. The computational results show the higher proportion of strategic passengers is, the smaller price increase the airline can adopt, and the higher proportion of high-valuation strategic passengers is, the larger price increase the airline can put to use under the same strategic level. If the proportion of low-valuation strategic passengers is higher, the price increase should be gentle and step by step when the price increase strategy is adopted. If the airline uses price-cut policy, the adjustment should be small. In addition, the high-valuation passenger mainly affects high-price periods and the low-valuation passenger mainly affects low-price periods. When the proportion of strategic passengers is fixed, the lower the passenger strategic level is, the larger the price slope is. These findings can provide some references for the airline to make more precise and flexible pricing decisions.

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Section: Literature Reviewmentioning

confidence: 99%

Dynamic air ticket pricing using reinforcement learning method

Gao

Fang

2022

RAIRO-Oper. Res.

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“…Other scholars focused on the choice of promotion strategies [28]. Some have studied the effect of promotion duration [36], while others have examined whether complementary strategies are better than current strategies across products. There are also studies on discount pricing, which focus on designing optimal discount policies to maximize the firm's profits [5,56], mainly seeking optimal discount pricing strategies to attract consumers in order to increase revenue.…”

Section: Promotion Strategy Analysismentioning

confidence: 99%

PromotionLens: Inspecting Promotion Strategies of Online E-commerce via Visual Analytics

Zhang¹,

Wang²,

Zhao³

et al. 2022

Preprint

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Fig. 1. Case I: (1) Select a product within the red circle among all 361°sneakers in the Product Overview. (2) Browse the product description of the selected product at the buttom of the scatter chart. (3) View the annual data of the selected product in the Promotion Overview. (4) Adjust the time period selector in the Sales Prediction View. (5) Look through the dotted lines and find non-overlapping zones. (6) Change the promotion strategy in the Strategy View -exchange the value discount that exists with the same discount rate and percentage discount for the time period. (7) Discover that sales have decreased. (8) Conclude that the value discounts may be appropriate for the selected product. (9) Compare similar products in the glyphs, word clouds and box plots in the Competitive Analysis View, and select another XTEP product. (10) Adjust the time selector to fix a time period for the newly selected product. (11) Replace the existing percentage discount in the Strategy View with the same discount rate and value discount for the time period. (12) Find that sales have decreased. ( 13) Conclude that the percentage discount may be appropriate for the selected product.

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“…Additionally, online sellers are endowed with tools to do that. For example, many online sellers have implemented coupons (Son, 2017; Li et al., 2020), and thus the follower difficultly observes the real price of the first‐mover. Therefore, we assume that the retailing prices are simultaneously set if there is market competition, which is in line with Abhishek et al.…”

Section: Modelmentioning

confidence: 99%

Interaction between the introduction strategy of the third‐party online channel and the choice of online sales format

Shi

Jiang

Wang

2021

Int Trans Operational Res

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On the online platform of e‐tailers (e.g., Amazon), there are many third‐party retailers who can resell products by paying e‐tailers a platform usage fee. When e‐tailers sell manufacturers’ products through the agency selling or reselling format, manufacturers may also sell the products via the third‐party retailers, i.e., the third‐party online channel. Therefore, in an online retailing supply chain composed of a manufacturer, an e‐tailer ad a third‐party retailer, this paper employs game theory to study the interaction between the introduction strategy of such channel and the choice of online sales format. The results show that under the agency selling format, the manufacturer should always introduce the channel to reduce the loss caused by platform usage fee and the low sales efficiency; under the reselling format, if the platform fee rate is small, the manufacturer will introduce such channel because of benefiting from downstream competition brought by the channel, otherwise, vice versa. When the channel is introduced under both sales formats and the sales efficiency of the manufacturer is not very high or very low, with the discount factor of consumer utility in this channel being large, the e‐tailer should choose the reselling format even if the platform fee rate is large. In case the channel is introduced only under the agency selling format and the sales efficiency of the manufacturer is not very high or very low, even if the platform fee rate is very large, the e‐tailer should also choose the reselling format. These choices always benefit the manufacturer (i.e., two win‐win situations). Under the agency selling format, the third‐party retailer should always improve the utility gained from purchasing from this channel, but it should keep the utility at an appropriate level under the reselling format.

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Two-period discount pricing strategies for an e-commerce platform with strategic consumers

Cited by 44 publications

References 37 publications

Dynamic air ticket pricing using reinforcement learning method

Dynamic air ticket pricing using reinforcement learning method

PromotionLens: Inspecting Promotion Strategies of Online E-commerce via Visual Analytics

Interaction between the introduction strategy of the third‐party online channel and the choice of online sales format

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