Optimal Pricing Decisions Research Articles

Impact of consumers’ anticipated regret on brand owners’ blockchain adoption in the presence of a secondhand market

Blockchain has been widely adopted in the field of product traceability owing to its powerful information tracing function. In this study, considering consumers’ anticipated regret (e.g., high-price regret and misfit regret), we investigate a brand owner’s (BO’s) blockchain adoption strategy under competition between new and secondhand products. Moreover, we identify the uncertainty mitigation effect and brand image improvement effect of blockchain adoption. Four scenarios are involved: Scenario NN (without blockchain and no anticipated regret), Scenario NH (without blockchain considering only high-price regret), Scenario NL (without blockchain considering only misfit regret), and Scenario B (with blockchain). We construct Stackelberg games to explore the optimal pricing decisions for BO and secondhand supplier (SS). The results indicate that, without blockchain adoption, alleviating high-price regret (or stimulating misfit regret) can enhance the profits of both BO and SS. BO does not necessarily benefit from blockchain adoption. Specifically, blockchain adoption increases BO’s profits if (1) the brand image improvement level is large, or (2) the brand image improvement level is moderate, and the high-price regret intensity is strong (or the misfit regret intensity is weak). Furthermore, under certain conditions, SS is able to become a free rider of BO’s blockchain adoption. Three extensions are analyzed to demonstrate that key findings are robust.

Trend-Chasing Versus Minimalism: Selling Fewer, Better Products to Fashion-Sensitive Customers

Fashion sellers are sometimes critiqued for selling low durability products, resulting in waste. Blame is also directed at consumers, who purchase new fashions despite having accumulated a closet full of prior fashions. The “slow fashion” movement encourages sellers to produce higher durable products, thus supporting less frequent purchases by consumers. Using an infinite-time model and considering strategic consumer behavior, including their ability to accumulate a “closet” of varieties over time, we analyze the seller’s profit-maximizing price and product-durability decisions. We initially assume a static price but later analyze the potential profit gains from dynamic pricing. When analyzing a heterogeneous consumer market, we initially allow customers to vary (distributed uniformly) in their sensitivity to fashion. Subsequently, we explore alternative distributions for consumers’ fashion sensitivity and the correlation between their fashion sensitivities and product valuations. Using this framework, we show how the seller’s optimal price and durability decisions yield distinct shopping segments, which we refer to as the minimalist versus trend-chasers. We find that if the degree of fashion uncertainty is moderate, the seller’s optimal choice of product durability will support the emergence of both behaviors. As the variety uncertainty expands, if the seller’s costs are sufficiently low, it will support a throwaway culture via disposable products. Otherwise, given high costs, the seller optimally targets a slow fashion-type outcome, with consumers targeting reuse (with durability) rather than variety. Our findings shed light on consumers’ optimal purchasing behaviors in relation to both market parameters and the firm’s pricing and durability decisions.

Comparison of competing supply chains with different structures under cap-and-trade regulation

To reduce carbon emissions, many countries and regions have implemented carbon cap-and-trade regulation. The main objective of this paper is to explore the economic and environmental impacts of carbon cap-and-trade regulation on two competing supply chains. This paper considers two cases: (i) in the absence of cap-and-trade regulation and (ii) with carbon cap-and-trade regulation. For each case, there are three structures: centralized-centralized (C-C) structure, decentralized-decentralized (D-D) structure, and hybrid centralized-decentralized (C-D) structure. First, this paper analyzes the optimal pricing decisions of two competing supply chains for the two cases, and then explores the impacts of cap-and-trade regulation on the sale price, market demand, economy (include enterprise profits and consumer surplus), environment (i.e., carbon emission) and total social welfare. Finally, numerical examples are provided to illustrate the theoretical results. By comparing the two cases, the main conclusions are as follows: (i) cap-and-trade regulation leads to the increase of unit price and the decrease of the market demand, (ii) cap-and-trade regulation leads to the reduction of both carbon emission and the consumer surplus, (iii) the impacts of cap-and-trade regulation on the profit and social welfare depend on the carbon cap.

Optimal two‐period pricing decisions and value‐added service strategies of two‐sided platform considering suppliers entry timing

AbstractThe flourishing platform business model has been rapidly integrated into manufacturing industries, and value‐added service (VAS) provided by the platforms has become a critical part of enhancing competitiveness. This study investigates the optimal two‐period pricing decisions and VAS strategies of the two‐sided platform for manufacturing. For both the supplier and manufacturer side, the platform decides the entry fees in each period and provides differentiated quality of basic services, as well as the VAS (if any). Moreover, the manufacturer's utility of accessing is influenced by the cross‐network externality, which is related to the number of suppliers in each period. In the presence of the supplier's varying entry timing, three VAS strategies are available for the platform including: (1) VAS for suppliers in Period 1 (Model S1), (2) VAS for suppliers in Period 2 (Model S2), and (3) VAS for manufacturers in Period 1 or 2 (Model M). We establish a two‐period game model under each VAS strategy. Then, the optimal platform's pricing decisions are derived, and the optimal performances in three VAS strategies are compared. Findings demonstrate that when the cross‐network externality strength is large, the platform always prefers Model S1; only when both the cross‐network externality strength and quality of the platform's basic service are comparatively low, the platform selects Model S2; otherwise, the platform chooses Model M. This study also extends to the scenario that the platform provides bilateral VAS in Period 1 (Model B1) or Period 2 (Model B2). Notably, the platform is not always willing to offer bilateral VAS, especially when the VAS cost coefficient is relatively high.

A pricing strategy of dual-channel supply chain considering online reviews and in-sale service

PurposeThe paper attempts to discuss the optimal pricing decisions under the decentralized and centralized decision and analyze the influence of online reviews and in-sale service on dual-channel supply chain. Finally, the authors design a two-part tariff coordination mechanism.Design/methodology/approachTo deal with this pricing conflict problems of dual-channel supply chain consisting of dominant manufacturer and a retailer, considering the fact that online reviews and in-sale service are important factors on consumers’ purchase decisions, the authors establish some basic models and exploit them to discuss the optimal pricing decisions under the decentralized and centralized decision and analyze the influence of online reviews and in-sale service on dual-channel supply chain. Finally, the authors design a profit-sharing coordination mechanism.FindingsThe results show that the optimal online direct selling price is positively correlated with product perceived quality obtained from online reviews and negatively correlated with the in-sale service. The traditional retail price is positively correlated with the in-sale service and weakly correlated with online reviews. For the manufacturer and retailer, whether decentralized decision or coordination contract, their profits increase with the increase of the in-sale service in a certain range and quality perceived from spontaneous online reviews. Online reviews and in-sale service are important factors on consumers’ purchase decisions. Positive in-sale services and online reviews can provide consumers with a better shopping experience, thereby promoting their enthusiasm for shopping and improving their quality of life. The two-part tariff coordination mechanism improves the profits of the manufacturer and the traditional retailer, respectively, through the transfer fee.Originality/valueThe proposed approach can well analyze the channel conflicts and pricing problems between retailers and manufacturers with respect to product offline price and online price. The analysis and results can inform decision-making for manufacturers and retailers.

Retracted: Optimal Pricing Decision of Fashion Apparel considering Experiential Service and Design Enhancement

Retracted: Optimal Pricing Decision of Fashion Apparel considering Experiential Service and Design Enhancement

Deterministic and probabilistic service-hailing mode choice for on-demand service platforms

To cater to the diverse needs of consumers, on-demand service platforms often provide vertically differentiated services and allow consumers to choose their preferred service class. In the traditional service-hailing mode, consumers choose from vertically differentiated services in a deterministic way. However, an emerging service mode bundles options to allow consumers to choose multiple classes of services simultaneously, after which the system assigns one class, which seems probabilistic from the consumer’s point of view. This paper elucidates the differences between the deterministic (DE) and probabilistic (PR) service-hailing modes in terms of the decision-making and profitability of the on-demand platform. It also investigates the platform’s optimal pricing decisions under the DE and PR modes and service mode choices. This paper constructs a stylized model capturing the participation and interaction behaviors of consumers and self-employed service agents, assuming endogenous supply and demand. The model is used to characterize the platform’s optimal price and wage decisions for vertically differentiated services. The results show that the platform’s pricing strategies and service targets are jointly determined by demand-side and supply-side factors, and whether the platform should adopt DE or PR mode is contingent on the consumers’ basic valuation level and its volatility. Furthermore, exploring a more complex hybrid mode suggests that introducing the bundled option does not necessarily boost the platform’s profit. Our findings offer meaningful insights into the pricing strategies and service-hailing mode selections of on-demand platforms offering vertically differentiated services.

Competing and Sharing: An Analysis of Optimal Pricing and Capacity Sharing Decisions in a Competitive Market

This research investigates the possibility for firms competing in the same market to willingly and profitably share their capacity. We consider two firms selling substitutable products in four different scenarios, according to their competition (non-competing or competing) and capacity sharing (with or without capacity sharing option) situations. In each scenario, each firm’s optimal capacity sharing and retail pricing strategies are characterized. Our results indicate that the two firms are willing to share their capacity only when the capacity selling firm has sufficiently large capacity while the capacity buying firm has sufficiently small capacity. The firms’ relative capacity in turn determine the optimal capacity sharing price, the exchanged capacity sharing quantity, and their retail prices in the market. Going against the common intuition, our results show that it can still be optimal for a firm to sell her capacity to her direct competitor even when she sets a capacity price lower than her retail price (i.e. she makes less per unit of capacity when selling it to the competitor rather than selling it in her own market). Furthermore, capacity sharing can cause the selling firm to willingly lower her retail price despite the smaller capacity she has left after selling some capacity to the competitor. Overall, our research suggests that capacity sharing is a viable and profitable mechanism to help firms selling substitutable products gain more profits and more effectively match their supplies with demand in the market.

Advance selling strategy and pricing decisions with online reviews

AbstractMotivated by marketing practices in advance selling, this paper studies the optimal pricing decisions and advance selling strategy with online reviews. The firm may charge a full or partial price in advance selling and then determine whether to continue selling products in the spot market. We characterize the equilibrium pricing decisions, selling scheme, and advance selling strategy in the monopoly market. We find that no matter what kind of advance selling strategy is implemented, the firm should choose the two‐period selling scheme instead of the one‐period one to market the product. Notably, when the two‐period selling scheme is chosen, either the skimming pricing or the penetration pricing may be optimal for the firm. Specifically, when the review valence is significantly lower, the skimming pricing is always favored by the firm; otherwise, the penetration pricing is more profitable. Moreover, the disclosure quality and review valence jointly affect the choice of firm's optimal advance selling strategy. In detail, advance selling with a full‐price strategy is always dominant if the disclosure quality is high; otherwise, the firm's optimal advance selling strategy is determined by the review valence. Meanwhile, we also analyze several extensions to explore meaningful insights and provide decision‐making support for the firm facing a complex marketing environment.

Optimal Pricing and Quality Decisions in Supply Chains With Consumers’ Anticipated Regret and Online Celebrity Retailers

Shopping on a live-streaming e-commerce platform has become a popular way of consumption. In this article, we build models to study the decision-making of online celebrity retailers (OCRs), taking into consideration consumers’ anticipated regret behaviors. We explore the OCRs optimal pricing and quality decisions under the basic models and further examine the OCRs sales efforts in the extended model. We investigate the impact of consumers’ anticipated regret behaviors on the OCRs profit. After that, we examine when the supply chain with the OCR can achieve the win–win outcome. To assess the robustness of the results, we conduct extensive numerical studies of the basic and extended models. We derive a counterintuitive result that negative consumers’ anticipated regret does not necessarily hurt the OCRs profit and consumer surplus. In addition, a low consumers’ search cost may instead lead to higher profit for the OCR. If the channel construction cost of the live-streaming platform is low, the OCRs product quality and price will decline. The OCRs costs of handling returns and maintaining sales channels can help the supply chain achieve the win–win outcome for both the OCR and consumers.

Optimal pricing decisions in a two echelon green/non-green resilient supply chain for substitute and complementary products considering disruption risk

Optimal pricing decisions in a two echelon green/non-green resilient supply chain for substitute and complementary products considering disruption risk

Pricing decision for recycling and remanufacturing supply chain considering consumer online consumption preferences and recycled products’ quality

With the organic integration of the Internet and remanufacturing industry, traditional manufacturers can recycle used products and sell products (including new and remanufactured products) through e-commerce retail platforms. A recycling and remanufacturing supply chain with three members (manufacturer, e-commerce retail platform, third-party recycler) is constructed in this paper. Manufacturer has remanufacturing capabilities, and the e-commerce retail platform can provide logistics service. In response to the organic integration of the Internet and remanufacturing industry, we mainly consider the pricing decisions of consumer preferences for online sales models and recycled products’ quality. Based on the impact of consumer used product recycling promotion activities on supply chain, a pricing game model was constructed for three recycling channels: manufacturer, e-commerce retail platform, and third-party recycler. Optimal pricing decision, logistics service level, used product recycling promotion intensity index, and recycling rate were obtained. Research has shown that consumer preferences can significantly improve supply chain logistics service level, pricing, market demand, and profits; Strengthening consumer awareness of remanufacturing used products and improving recycled products’ quality can not only lower consumer purchase prices and expand consumer demand, but also increase profits of supply chain members.

Optimal Pricing and Quality Decisions Under Cooperative Promotion of Cross-Market Service Platforms

Optimal Pricing and Quality Decisions Under Cooperative Promotion of Cross-Market Service Platforms

Dynamic pricing and emission reduction efforts in a dual-channel green supply chain under bidirectional free riding

In this study, a tripartite dynamic game framework is introduced to address the joint carbon reduction challenges among green supply chain members and the bidirectional free-riding behavior of digital and brick-and-mortar retailers. The model specifically involves a manufacturer, a digital retailer, and a brick-and-mortar retailer, examining their optimal pricing and emission reduction decisions, as well as the extent of the bidirectional free-riding effect. The findings indicate that both the manufacturer's enhancement of emission reduction efforts and the retailers' amplification of their promotional endeavors result in increased prices and profits. The influence of a retailer's low-carbon reputation on the manufacturer's carbon reduction initiatives depends on the impact of the manufacturer's own emission reduction level on their efforts. Furthermore, due to the bidirectional free-riding phenomenon, the effect of the digital (brick-and-mortar) retailer's low-carbon reputation on the promotional efforts of the brick-and-mortar (digital) retailer relies on the influence of their own low-carbon reputation on their promotional initiatives. In addition, the bidirectional free-riding behavior of digital and brick-and-mortar retailers is closely associated with factors such as the coefficient of the retailer's promotional effort level, the coefficient of the retailer's promotional cost, the attenuation rate of low-carbon reputation, and other parameters.

A hybrid trade-old-for-new and trade-old-for-remanufactured supply chain with carbon tax

Facing serious environmental problems, governments and manufacturers are taking action to reduce carbon emissions. Among these endeavors, carbon tax policy are widely adopted by governments, trade-old-for-new (TON) and trade-old-for- remanufactured (TOR) are offered by manufacturers and subsidized by governments. To explore the effects of remanufacturer competition and carbon tax on the manufacturer’s TON and TOR decisions and the environment, we formulate three profit maximization models and present some theoretical and numerical analyses. The results show that, under the remanufacturer competition and carbon tax, the manufacturer’s optimal price and production decisions mainly depend on consumer willingness and carbon tax rate. A higher consumer willingness to manufacturer’s remanufactured products will decrease the demand for the manufacturer’s TON, but it always increases the demand foe the manufacturer’s TOR. A higher consumer willingness to remanufacturer’s products will not affect the demand for the manufacturer’s TON; however, it will reduce the demand for manufacturer’s TOR. In addition, we find that a higher carbon tax rate always reduces total carbon emission reduction, and it may increase the manufacturer’s profit due to the increase in TOR demand.

The consumer web-rooming on different sales models and retailing channel expansion

In the context of multichannel retailing, the phenomenon of web-rooming, where consumers research online and purchase offline, has become widespread. Therefore, we consider supply chain consisting of a manufacturer, an e-commerce platform, and an offline retailer, we study the impact of consumer web-rooming effect on the three sales modes of online channels, which are directly operated by the manufacturer, resold by the e-commerce platform, or co-exist with direct operation and resale, and comparatively analyze the pricing, demand, and profit of each channel under the three modes. The conditions for optimal pricing decisions are further explored through numerical simulation. It is found that profit always increases whether the online channel is opened by the manufacturer or the e-commerce company. The coexistence of direct sales and resale does not always increase profit for offline retailers, which must be discussed in the context of the sales model before channel expansion. The existence of web-rooming not only affects the decision-making of manufacturers and e-commerce platforms, but also always harms the interests of e-commerce platforms, and as the intensity of web-rooming deepens, the revenue of e-commerce platforms becomes smaller. Offline retailers benefit from web-rooming and experience a slowdown in profit growth as the intensity of the phenomenon increases. For manufacturers, the impact of changes in the intensity of the web-rooming is analyzed in relation to platform commission rates and online retail prices.

Analysis of Green Innovation of the E-Tailer and Supplier with a Drop Shipping Option in E-Commerce

As customer demand for green products increases in the digital economic era, this study analyses the green innovation of the e-tailer and supplier in drop shipping models. Moreover, drop shipping e-tailers and suppliers with a drop shipping option need to make choices regarding whether to provide green or normal products to the market. When a supplier with a drop shipping option produces green products, more fees may be invested in the production of green products than on normal products. The drop shipping e-tailers and suppliers with a drop shipping option can also choose to sell normal products at a low cost, as before. This study designs four models of drop shipping e-tailers and suppliers with a drop shipping option under different choices, analyzes their operational process in drop shipping models, and investigates five theorems. The optimal pricing decisions and green degree of drop shipping e-tailers and suppliers with a drop shipping option were evaluated in this study. The impacts of the green innovation factor, green elasticity coefficient, manufacturing and distribution costs on the drop shipping e-tailers and suppliers with a drop shipping option, and the effect of other environmental parameters on the green degree of green products are also analyzed through computer simulation. The findings of the simulation analysis provide valuable guidance for e-tailers and suppliers with green innovation in drop shipping models and offer important academic and practical implications for e-commerce and the digital economy.

Optimal pricing decisions of centralized dual-channel supply chains in a duopoly: a study on the influence of competition structure

Optimal pricing decisions of centralized dual-channel supply chains in a duopoly: a study on the influence of competition structure

Tripartite Evolutionary Game Analysis and Mode Selection of Reward-Based Crowdfunding From the Perspective of Value Co-Creation

Crowdfunding refers to releasing fund-raising projects and raising funds through the Internet. To explore the relationship between platform resource investment and value creation in interactive learning between initiators and supporters, this article constructs a three-party game model among the platform, supporters, and the initiator, based on evolutionary game theory, and then obtains the replicator dynamics function of the player and analyzes the evolution trend. Further, this article analyzes the optimal pricing decision of the platform and the initiator under different crowdfunding modes and its optimal mode. The results show that there are two Evolutionary Stable Strategies that are accepted by three players under certain parameters, and the equilibrium point remains stable under external interference. When the net income of initiators participating in value co-creation increases, it can promote the crowdfunding platform to actively participate in the value co-creation process, while it will inhibit the participation of the platform when the net loss of initiators participating in value co-creation increases. In addition, although supporters will also be affected by the willingness of the platform to participate in value co-creation, the willingness of initiators to participate has a greater impact on supporters. As for the mode selection, when the platform does not provide fee preference, considering that the prices of the initiators in the crowdfunding period are the same, single-stage crowdfunding is the dominant mode, and the income of the platform and the initiators is also higher than that under the two-stage crowdfunding. When the product price in the single-stage crowdfunding period is lower than that in the two-stage sales period, the two-stage crowdfunding is the best choice for the initiator.

Is AI testing beneficial for the manufacturer and social welfare? Optimal test strategy of a smart product

The rapid technological revolution of Industry 4.0 has set off rapid advancement in the smart product development. Testing the smart product’s system before release to market is crucial for ensuring proper functioning. Smart product manufacturers must carefully consider different testing modes to choose the optimal one based on product characteristics and consumer’s shopping intention. Additionally, different testing modes have varying impacts on the environment and social welfare, as well as profitability of the product. This study utilizes a two-period game theory model to analyze a smart product manufacturer’s optimal testing mode and pricing decision. Three testing mode are evaluated: manual testing mode (MT mode), artificial intelligence testing mode (AT mode), and public testing mode (PT mode). Consumers’ utility is influenced by factors such as consumer preferences, product quality, usage duration, and network externality effect. Our findings indicate that the optimal testing mode depends on quality improvement and network effect coefficients. Specifically, when the degree of quality improvement is high and the network effect is moderate, MT mode is preferred; when the quality improvement is high but the network effect is small, AT mode dominates; under other conditions, PT mode is optimal. Quality improvement and network effect coefficients have similar effects on pricing decisions but impact the profits in different manners. Social welfare is the highest under MT mode when the network effect is high and quality improvement is low, under AT mode when network effect is low and quality improvement is high, and under PT mode when both factors are high or low. Finally we provide a numerical example of how profit-driven business decisions may conflict with social welfare, potentially leading to lower social welfare than the theoretical optimum under the chosen testing mode strategy.