Dynamic Pricing of New Experience Products with Dual-channel Social Learning and Online Review Manipulations

Omega ◽  
2022 ◽  
pp. 102592
Author(s):  
Qiaozhen Guo ◽  
Ying-Ju Chen ◽  
Wei Huang
Keyword(s):  
Social Learning ◽  
Dynamic Pricing ◽  
Online Review ◽  
Dual Channel

Dynamic pricing and coupon promotion strategies in a dual-channel supply chain based on differential game

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zonghuo Li ◽  
Wensheng Yang ◽  
Yinyuan Si
Keyword(s):  
Supply Chain ◽  
Differential Game ◽  
Dynamic Pricing ◽  
Brand Image ◽  
Content Type ◽  
Dual Channel ◽  
Promotion Policies ◽  
Promotion Strategies ◽  
Joint Pricing ◽  
Dual Channel Supply Chain

PurposeThis paper investigates a dual-channel supply chain in which a manufacturer offers coupons in the online channel and the retailer in the offline channel. The optimal pricing and coupon promotion policies are explored, and the brand image under different promotion scenarios is studied.Design/methodology/approachThree differential game models, namely no coupon is offered, coupons offered by the manufacturer and coupons offered by the retailer, are constructed.FindingsThe results show that the manufacturer and retailer intend to conduct coupon promotions under a large coupon redemption rate. Coupon promotion derives a higher price and profit for the issuers, and the manufacturer can free-ride on the retailer's coupon promotion. The retailer's profit in the retailer-promotion scenario may be lower than that in the manufacturer-promotion scenario in some special conditions. Besides, price, coupon face value, brand image and profit increase over time. After multiple cycles game, the operational strategy evolves to an optimal equilibrium status.Originality/valueThis paper provides guidance and advice for dual-channel supply enterprises to implement joint pricing and coupon promotion strategies under multiple sales seasons.

Study and Simulation on Dynamics of a Risk-Averse Supply Chain Pricing Model with Dual-Channel and Incomplete Information

2016 ◽  
Vol 26 (09) ◽  
pp. 1650146 ◽  
Author(s):  
Lijian Sun ◽  
Junhai Ma
Keyword(s):  
Supply Chain ◽  
Incomplete Information ◽  
Dynamic Pricing ◽  
Wholesale Price ◽  
Price Adjustment ◽  
Phase Portraits ◽  
Largest Lyapunov Exponent ◽  
Risk Averse ◽  
Dual Channel ◽  
Adjustment Speed

Under the industrial background of dual-channel, volatility in demand of consumers, we use the theory of bifurcations and numerical simulation tools to investigate the dynamic pricing game in a dual-channel supply chain with risk-averse behavior and incomplete information. Due to volatility of demand of consumers, we consider all the players in the supply chain are risk-averse. We assume there exist Bertrand game and Manufacturers’ Stackelberg in the chain which are closer to reality. The main objective of the paper is to investigate the complex influence of the decision parameters such as wholesale price adjustment speed, risk preference and service value on stability of the risk-averse supply chain and average utilities of all the players. We lay emphasis on the influence of chaos on average utilities of all the players which did not appear in previous studies. The dynamic phenomena, such as the bifurcation, chaos and sensitivity to initial values are analyzed by 2D bifurcation phase portraits, Double Largest Lyapunov exponent, basins of attraction and so on. The study shows that the manufacturers should slow down their wholesale price adjustment speed to get more utilities, if the manufacturers are willing to take on more risk, they will get more profits, but they must keep their wholesale prices in a certain range in order to maintain the market stability.

scholarly journals Dynamic Pricing Game in a Dual-channel Closed-loop Supply Chain with Heterogeneous Players and Delay Decision

2021 ◽  
Author(s):  
Yuhao Zhang ◽  
Tao Zhang
Keyword(s):  
Supply Chain ◽  
Nash Equilibrium ◽  
Dynamic Pricing ◽  
Closed Loop ◽  
Stackelberg Game ◽  
Consumer Preference ◽  
Direct Channel ◽  
Closed Loop Supply Chain ◽  
Dual Channel ◽  
Delay Decision

Abstract In this paper, we study a dual-channel closed-loop supply chain(CLSC), where the manufacturer wholesales the new product through the traditional retail channel and distributes the remanufactured product via a direct channel established by himself. We focus on developing two dynamic Stackelberg game models under the assumption of the retailer is an adaptive agent and the manufacturer is a bounded rational player with non-delay and delay decisions. The existence and locally asymptotic stability of Nash equilibrium is investigated, and also the complex dynamics of each model is illustrated including period-doubling bifurcation, Neimark-Sacker bifurcation, strange attractor and chaotic phenomena. Numerical simulations are conducted to examine the impacts of key parameters on the complex behaviors of the long-run dynamic Stackelberg game and the performance of chain members under various scenarios. The results reveal that the excessively high value of the price adjustment speed of the manufacturer, the consumer discount perception for the remanufactured product as well as the consumer preference degree to the direct channel have adestabilization effect on the Nash equilibrium. Besides, the delay decision adopted by manufacturer no matter in the traditional or direct channel does not always necessarily make the system more stable, but the appropriately delay weights can expand the stability domain of the system. Moreover, the manufacturer would suffer a significant profit loss while the retailer can capture more profits when the dual-channel CLSC system falls into periodic cycles and chaos motions. At last, the variable feedback control method is utilized to eliminate the delayed system chaos.

Fixed, flexible, and dynamics pricing decisions of Airbnb mode with social learning

2020 ◽  
pp. 135481661989695 ◽  
Author(s):  
Yuting Chen ◽  
Rong Zhang ◽  
Bin Liu
Keyword(s):  
Social Learning ◽  
Dynamic Pricing ◽  
Positive Impact ◽  
Sharing Economy ◽  
Competitive Market ◽  
Risk Level ◽  
Risk Sensitivity ◽  
Peak Period ◽  
Pricing Decisions ◽  
Pricing Decision

The rise of the sharing economy has changed the traditional way of providing service to consumers. Airbnb is the most successful peer-to-peer model in the hospitality industry. This article investigates how to conduct strategic dynamic pricing in a competitive market by considering market conditions, quality, and risk sensitivity. Our research yields three main conclusions. First, we observe that the higher the risk level suppliers face, the more profit they will get; the lower the risk level consumers face, the more utilities they obtain. Second, we find that fixed pricing may be optimal or near-optimal for the platform when market size is small, the accommodation quality is better, and consumers’ reliability is low. Otherwise, a flexible pricing strategy is optimal. Finally, we extend the research into dynamic pricing decision in presence of Bayesian social learning and propose that the less-perfect accommodation requires social learning more urgently. In tourism peak period, social learning has less positive impact when the Airbnb accommodation is much perfect. These conclusions provide useful guidance on how the Airbnb and hotel can take advantage of the competitive market.

The Love of Large Numbers: A Popularity Bias in Consumer Choice

2017 ◽  
Vol 28 (10) ◽  
pp. 1432-1442 ◽  
Author(s):  
Derek Powell ◽  
Jingqi Yu ◽  
Melissa DeWolf ◽  
Keith J. Holyoak
Keyword(s):  
Social Learning ◽  
Statistical Model ◽  
Consumer Choice ◽  
Prior Information ◽  
Statistical Information ◽  
Online Review ◽  
The Internet ◽  
Statistical Inferences ◽  
Large Numbers ◽  
Potential Indicator

Social learning—the ability to learn from observing the decisions of other people and the outcomes of those decisions—is fundamental to human evolutionary and cultural success. The Internet now provides social evidence on an unprecedented scale. However, properly utilizing this evidence requires a capacity for statistical inference. We examined how people’s interpretation of online review scores is influenced by the numbers of reviews—a potential indicator both of an item’s popularity and of the precision of the average review score. Our task was designed to pit statistical information against social information. We modeled the behavior of an “intuitive statistician” using empirical prior information from millions of reviews posted on Amazon.com and then compared the model’s predictions with the behavior of experimental participants. Under certain conditions, people preferred a product with more reviews to one with fewer reviews even though the statistical model indicated that the latter was likely to be of higher quality than the former. Overall, participants’ judgments suggested that they failed to make meaningful statistical inferences.

scholarly journals Dynamic Pricing in the Presence of Social Learning and Strategic Consumers

2017 ◽  
Vol 63 (4) ◽  
pp. 919-939 ◽  
Author(s):  
Yiangos Papanastasiou ◽  
Nicos Savva
Keyword(s):  
Social Learning ◽  
Dynamic Pricing ◽  
Strategic Consumers
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