Optimal presale strategy considering consumers’ preference reversal or inconsistency

Wang, Xiaohuan; Tian, Jiaqi; Fan, Zhi‐Ping

doi:10.1016/j.cie.2020.106581

Cited by 15 publications

(13 citation statements)

References 48 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Jiang et al [ 17 ] explore the impact of consumer out-of-stock regret on product presale pricing and retailer profitability. Wang et al [ 18 ] measure consumer utility based on time preference and compare four presale strategy models to maximize seller revenue. Zou [ 19 ] reports that in the face of market competition and information asymmetry, retailers adopt a reverse presale model that promotes the retailer’s market share while increasing the enterprise’s profits and order quantity.…”

Section: Literature Reviewmentioning

confidence: 99%

Selection of presale models for innovative products considering channel preferences and valuation differences

Jiang,

Qin,

Zuo

et al. 2024

PLoS ONE

View full text Add to dashboard Cite

To reduce financial pressure and operational risk, and improve match between supply and demand, an increasing number of enterprises are adopting presales to launch new products. In this context, this paper investigates three presale models for innovative products, namely, the no-presale model, the manufacturer presale model and the retailer presale model. A Hotelling model is used to describe the impact of channel preferences and valuation differences on the two-stage competition between innovative products. Aiming at evaluating the purchase behavior of consumers under three presale modes, a game optimization model is established to analyze the presale decision problem for innovative products under different presale entities. The research shows that: (1) Compared with no-presale, presales can help enterprises obtain more profits. The overall profit of the supply chain is optimal under the retailer presale mode. (2) When the difference in channel preferences is small, the manufacturer obtains the greatest profit by choosing the direct presale model. In contrast, the selection of different presale entities has a significant impact on product sales and supply chain enterprise profits. At this point, the manufacturer should choose the retailer presale model. (3) When the product valuation discount is high, the manufacturer can increase the spot and wholesale prices to induce consumers to choose the presale method to purchase the product. In the opposite situation, the manufacturer should lower the presale price to improve the presale utility of consumers and encourage them to participate in the presale. These conclusions provide more targeted suggestions for enterprises to formulate presale strategies, which can help them grasp market demand and improve market competitiveness.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Selection of presale models for innovative products considering channel preferences and valuation differences

Jiang,

Qin,

Zuo

et al. 2024

PLoS ONE

View full text Add to dashboard Cite

show abstract

“…The interaction between advance selling and refund policies significantly affects retailer profits (Sun et al, 2018), and these refunds typically encompass both partial and full refunds. Wang et al (2020) measured consumer utility based on time preferences and analyzed the choice of seller's two‐stage pure pre‐sale (TP), one‐stage pure pre‐sale (SP), two‐stage hybrid pre‐sale (TH), and one‐stage hybrid pre‐sale (SH) models. Kuang and Jiang (2023) considered consumer purchase behaviors with temporal inconsistency and analyzed the pre‐sale equilibrium decisions of firms under no‐return, partial refund, and full refund scenarios.…”

Section: Literature Reviewmentioning

confidence: 99%

Pricing and outsourcing strategies in different online sales models within a co‐opetitive supply chain

Shi,

Xu,

Shan

2023

Manage Decis Econ

View full text Add to dashboard Cite

We examine a dual‐tier supply chain where the brand entrusts its production to competitive and non‐competitive manufacturers. We explore three online sales models used by the brand and manufacturers: traditional, pre‐sale, and hybrid. Manufacturers serve the brand while competing with their own products. Considering consumer valuations across models, we create Stackelberg and Nash models. We analyze consumer valuation impact and the interplay of sales models and structural configurations on operational efficiency. We find that with competitive manufacturers' lower pricing, retailers tend to outsource to them. Retailers can choose sales models based on consumer evaluations, and higher dominance enhances profitability.

show abstract

“…The continuous development of e-commerce makes competition in the market particularly fierce, leading to the majority of enterprises beginning to adopt a presale strategy to increase sales. Numerous models for pricing strategy in presale mode have been developed [23][24][25].…”

Section: Presale Strategies and Pricing Mechanismmentioning

confidence: 99%

Distributed Dynamic Pricing Strategy Based on Deep Reinforcement Learning Approach in a Presale Mechanism

Liang

Dong-jun

et al. 2023

Sustainability

View full text Add to dashboard Cite

Despite the emergence of a presale mechanism that reduces manufacturing and ordering risks for retailers, optimizing the real-time pricing strategy in this mechanism and unknown demand environment remains an unsolved issue. Consequently, we propose an automatic real-time pricing system for e-retailers under the inventory backlog impact in the presale mode, using deep reinforcement learning technology based on the Dueling DQN algorithm. This system models the multicycle pricing problem with a finite sales horizon as a Markov decision process (MDP) to cope with the uncertain environment. We train and evaluate the proposed environment and agent in a simulation environment and compare it with two tabular reinforcement learning algorithms (Q-learning and SARSA). The computational results demonstrate that our proposed real-time pricing learning framework for joint inventory impact can effectively maximize retailers’ profits and has universal applicability to a wide range of presale models. Furthermore, according to a series of experiments, we find that retailers should not neglect the impact of the presale or previous prices on consumers’ purchase behavior. If consumers pay more attention to past prices, the retailer must decrease the current price. When the cost of inventory backlog increases, they need to offer deeper discounts in the early selling period. Additionally, introducing blockchain technology can improve the transparency of commodity traceability information, thus increasing consumer demand for purchase.

show abstract

Optimal presale strategy considering consumers’ preference reversal or inconsistency

Cited by 15 publications

References 48 publications

Selection of presale models for innovative products considering channel preferences and valuation differences

Selection of presale models for innovative products considering channel preferences and valuation differences

Pricing and outsourcing strategies in different online sales models within a co‐opetitive supply chain

Distributed Dynamic Pricing Strategy Based on Deep Reinforcement Learning Approach in a Presale Mechanism

Contact Info

Product

Resources

About