Retail Pricing Strategies Research Articles

The pricing and sourcing strategies of competitive retailers under supply disruption in the presence of liquidated damages

Supply disruptions often make retailers face stock-outs and lead to higher selling price, which forcing retailers to adopt optimal sourcing strategies to avoid disruptions and carefully adjust their pricing when disruptions occur to achieve ideal profits in competition with other peers. In this paper, we optimize the combination of pricing levels and sourcing strategy of the competitive retailer having choices of cost or stable supplier when supply disruptions occur with the consideration of liquidated damages. Based on the procurement costs difference between retailers and competitors, we studied the optimal sourcing and pricing strategies under two types of Stackelberg game and one type of Nash game. We find that the Nash Equilibrium leads lower selling prices for retailers and larger purchases from cost suppliers compared to the Stackelberg game, but with the increase of retailer’s market potential, retailers gradually depend on stable suppliers. We also find that liquidated damages can have a significant impact on retailers’ decisions. Specifically, when the probability of disruption is high, retailers will mainly rely on stable suppliers in the presence of no liquidated damages, while in the case of liquidated damages, retailers will instead rely on cost suppliers. Furthermore, as liquidated damages increase, retailers prefer to source from cost suppliers and use very high price adjustments to account for supply disruptions. Especially when the risk of disruption is high, retailers rely mainly on cost suppliers and super high price adjustments. This highlights the critical role of liquidated damages on retailers’ optimal pricing and sourcing strategies.

A classified retail pricing and production scheduling model for industrial customers

In the electricity retail market, it’s an important operation way for a retailer to provide diversified services and design appropriate retail pricing strategies that stimulate demand side responses in order to increase profit and maintain customer welfare. This paper proposes a novel retail contract design that a retailer can adopt to provide different time-of-use (TOU) prices for the various types of industrial customers based on their adjustabilities and a part of rewards from the demand response (DR) market to those who respond to the urgent electricity requirements. A bi-level optimization model of retail pricing for classified industrial customers is set up based on their adjustable capacities of production process operations. At the upper level, the retailer’s benefit is maximized considering the stochastic risks of load fluctuation and the spot market. This is achieved based on the electricity consumption strategies of classified industrial consumers, which are obtained from the lower level. Decisions are then made concerning purchases from the spot market and retail pricing strategies for industrial customers. Based on the retail prices from the upper level and industrial production processes modeling, the model at the lower level takes the maximum industrial user’s benefit as the objective to obtain the electricity consumption scheme of each type of industrial user. The model optimizes both the time division and price level of retail TOU prices, resulting in detailed electricity consumption strategies for all types of industrial customers. The results of the cases show that the proposed retail pricing can improve adjustable capacities of industrial production process operations, effectively smooth the load curve of the retailer by making full use of the peak-load-staggered among industrial customers, and boost profits of both the retailer and industrial customers. Thus, a mutually beneficial situation between the retailer and industrial customers is realized.

Pricing and insurance strategy of online retailers for the price adjustment protection policy

Pricing and insurance strategy of online retailers for the price adjustment protection policy

The Impact of Return Shipping Insurance on a Retailer Based on Restricting Rights

In e-commerce, retailers often use return shipping insurance (RSI) to solve consumer returns, leading to a high return rate. To reduce this negative effect, we consider restricting rights to restrict consumers from obtaining RSI or buying products. We examine the effect of RSI on retail pricing strategies and profits under restricting rights. We formulate a game-theoretical model which consists of one insurer, a retailer and two types of consumers (informed consumers and uninformed consumers). By solving the model, we find that even though the insurer has restricted uninformed consumers from obtaining RSI, the retailer further restricts them from buying the product when the salvage value is low. Second, when the retailer and insurer have no right to restrict uninformed consumers, purchasing RSI may hurt the retailer. Third, when the insurer restricts uninformed consumers and the product salvage is low, the retailer adopts the high-price strategy; otherwise, the retailer adopts the low-price strategy. Finally, when the product salvage is low, the retailer will prevent uninformed consumers from buying the product by adopting the high-price strategy or using the restricting right. In this case, the insurer will set a higher premium.

Optimal pricing strategy of retailers considering speculative customers’ add-on items return behavior with cross-store full-reduction promotion

This purpose of the paper is to explore the optimal price strategy for the retailers under the cross-store full-reduction promotion mode, where speculative consumers will deliberately purchase add-on items to qualify for discounts when the purchase amount is less than the “full-reduction” threshold and then return the add-on items after successful payment. With respect to the optimal decision problem consisting of two online complementary retailers and an e-commerce platform in the face of speculative consumers’ add-on items return behavior, we construct the single-cycle sales decision models based on the revenue sharing contract. Furthermore, through the derivative function analysis method, we examine the effect of the proportion of speculative consumers, the proportion of product sharing discount amount and revenue sharing coefficient on the platform’s sale strategy and the retailers’ the optimal price strategy. The results show that whether platform implements cross-store full-reduction promotion strategy or not, the product price increases with the increase of revenue sharing coefficient. In addition, under the non-promotion sales mode, the optimal price is not affected by the speculative consumers’ behavior. Under the cross-store full-reduction promotion sales mode, the optimal price changes with the proportion of product sharing discount amount and the proportion of speculative consumers. And the price of only purchasing single product in this case is always higher than the price under the non-promotion sales mode. Finally, we compare the profits under the two scenarios, it is found that the profits under the cross-store full-reduction promotion sales mode are not always higher than that under non-promotion sales mode and the boundary conditions for the platform to adopt different modes are further given.

Consumer Loyalty Programs and Retail Prices: Evidence from Gasoline Markets

We study the pricing strategy of retailers that promote their sales with a loyalty program.

Residential customers-oriented customized electricity retail pricing design

As the retail market becomes more competitive, it is significant for retailers to present a proper and attractive retail pricing strategy. This paper proposes a two-stage customized retail pricing design based on personalized demand response incentives for different residential users. To accurately simulate the load variation according to the price change, the real-time elasticity concept has been first introduced into the framework of customizing retail prices. The utilization of customizing prices is to make better use of the price elasticity to encourage the load shifting of end-users and their active engagement in demand response. In the first stage, the retail price base value is obtained by simultaneously optimizing the time-of-use (ToU) structure and corresponding price level. The second stage focuses on the load redistribution caused by individualized price incentives, and the retail price revision is set. The two-stage solution results are combined to obtain the final customized retail electricity price plans. To verify the feasibility and effectiveness of the proposed method, the customized retail pricing scheme is tested with 30 selected users. Compared with the traditional unified retail pricing method, the total retail profit increases by 10.62%, and the total retail conditional value at risk (CVaR) and consumers’ payment decrease by 27.69% and 3.82%, respectively through the proposed customizing retail price method. The numerical results prove that through the proposed retail pricing method the retailing profit has increased, while the consumers' payment and risk management have also been guaranteed.

Pricing Strategy for Green Products Based on Disparities in Energy Consumption

The energy consumption disparity is an important factor affecting product pricing. The risk and the cost of new energy products are generally higher than those of traditional energy products, which results in conflicting pricing strategies between manufacturers and retailers. Applying the concepts from dynamic cooperative game theory, such as improved Shapley value, in this paper, we have studied the optimal pricing strategies of manufacturers and retailers in a cooperative and a noncooperative game. Based on policies and market conditions in China, we have used a logistic regression model to determine the impact of product sales, devised pricing strategies affected by the relevant government tax, and subsidy policy. The results show that, first, under the basic condition in which the manufacturer obtains profit, the optimal pricing of the retailer in a noncooperative game is more than that in a cooperative game. Second, the differential coefficient of the energy consumption of the two products in the cooperative game is greater than that in the noncooperative game. Third, the cooperative game not only plays an incentivizing role for retailers in setting reasonable prices of new energy products but also encourages manufacturers, producing a greater difference of energy consumption between traditional energy products and new energy products, which further reduces the consumption of new energy products. Finally, the strategies of sharing the green marketing costs by manufacturers and retailers can improve the total profits of the supply chain in addition to their own.

Pricing Decisions in Dual‐Channel Supply Chain considering Different Fairness Preferences and Low‐Carbon Advertising Level

Countries around the world advocate low‐carbon, green, and environmentally friendly lifestyles to combat climate change, which provides clear direction for enterprise decisions. This paper studies a low‐carbon dual‐channel supply chain based on behavioral economics, incentive theory, and optimization models to better formulate pricing decisions. This paper constructs a fair and neutral decentralized decision‐making model (FNDD), a decentralized decision‐making model considering Nash bargaining fairness concerns (NBFDD), a decentralized decision‐making model considering absolute fairness concerns (AFDD), and a fair and neutral centralized decision‐making model (FNCD) considering consumer preferences and the situations where supply chain members are fairness concerns or fairness neutrality. This paper analyzes the effect of low‐carbon advertising level on pricing strategies of online retailers and offline stores and compares pricing strategies of online retailers and offline stores in four decisions. The results show that Nash bargaining fairness concerns of supply chain members could effectively reduce the retail price of low‐carbon products and increase their sales volumes. Absolute fairness concerns intensify the dual marginal effect of decentralized decision‐making.

Inter-organizational contract control of advertising strategies in the supply chain

<p style='text-indent:20px;'>Advertising has a crucial impact on a product's goodwill. To further improve a product's goodwill and make more profit, member firms in the supply chain use various contracts to coordinate the channel. Considering the dynamic effect of advertising, this paper studies a two-level supply chain consisting of one manufacturer and one retailer. The two members focus on maximizing their profits through advertising and pricing strategies under two types of contracts: the wholesale price contract and the consignment contract. The Stackelberg differential game is introduced, and the optimal advertising effort, wholesale and retail pricing strategies in the two situations are studied. Numerical examples and sensitivity analyses are conducted to explore the models further. The results show that the retailer's revenue proportion and the product's goodwill according to consumers significantly affect the strategies and the contract choice of the partner firms in the supply chain. A proportion of too high or too low revenue may lead to a contract selection conflict between the two partner firms. However, when consumers care more about the product's goodwill, this contract selection conflict can be weakened.</p>

Stackelberg Game Perspective on Pricing Decision of a Dual‐Channel Supply Chain with Live Broadcast Sales

Focusing on the dual‐channel supply chain with live broadcasts selling, this paper investigates the service overflow of live broadcasts with Stackelberg game perspective and the impact of retailers’ different market potentials on the pricing decisions of dual‐channel members. Meanwhile, it also evaluates the pricing strategy of online retailers after introducing KOL (Key Opinion Leader) live broadcasts. The results show that when one of the dual‐channel retailers adopts live broadcast sales, the live broadcast service overflow will have an adverse impact on it, but the degree of the impact depends on the market potential of supply chain members, and different power structures can be used to offset the adverse impact of live broadcast service overflow. Then, the live broadcast sales service overflow will have a certain beneficial impact on online retailers under certain circumstances. Furthermore, with the increase of live broadcast sales service overflow, the retail prices of both companies will decline, while the live broadcast sales service overflow is more beneficial for consumers.

Research on Dual-Channel Supply Chain Promotion Strategy

The establishment of online direct sales channels influences the selection of pricing strategies and promotion information disclosure strategies of manufacturers and retailers. Considering the consideration of consumer preference, this paper studies the influence of different promotion information disclosure modes on the promotion effect and the income of supply chain members in the dual-channel supply chain with direct online channels. Based on hoteling model, the authors establish a model on market demand of the two channels and analyze the pricing and disclosure strategies of manufacturers and retailers under different concerns of consumers. It is found that there is a unique equilibrium threshold between the two disclosure modes. Only when the selling price after promotion is lower than the threshold are manufacturers or retailers willing to make information disclosure. It is also found that the disclosure intention and strategy of manufacturer or retailer will change with different customers' concerns and the relationship between the difference of two channels promotion and the threshold value.

Not Just About Price: Whether Consumers Seek Quality or Taste Determines Their Response to Retailer Pricing Strategies

Current models of the consumer response to retailer pricing strategies focus on how they impact price perceptions and retailer preferences. While intuitive, this perspective overlooks perceptions of value, which are a function of the benefits consumers acquire relative to price. We argue that the type of benefit consumers seek interacts with pricing strategy to impact consumers’ value perceptions and ultimately, retailer preference. We distinguish between quality benefits (subject to vertical differentiation) and taste benefits (subject to horizontal differentiation), and note that the type of benefit a consumer seeks impacts the value that they are able to obtain under different retail pricing strategies. We demonstrate that, all else equal, when consumers seek quality benefits, they prefer retailers that use discounts, but when consumers seek taste benefits, they prefer retailers that rely on every-day-low-pricing. We report a series of experiments and an analysis of consumer panel data to examine the proposed relationship between type of benefit sought and retailer preference, the mediating role of value, and managerially relevant moderators: cherry-picking cost, the relationship between price and quality, and discount pattern.

An agent-based simulation for a trade-off between frequency and depth in retail price promotion strategy

Abstract A good pricing strategy helps retailers generate profits, increase sales, and set a strategic position in the market. However, the interactions between retailers and customers add complexity to retailer pricing decisions. This study aims to model retail pricing complexity and analyse retail pricing strategies using an agent-based simulation approach. Two types of agents are modelled: customers and retailers. Customer buying decisions are influenced by several customer preferences factors, while product prices are set according to the retailer’s promotion strategy. The promotion is applied based on the frequency and depth of the price cut. A functional product market is considered in this simulation, representing daily necessities that are purchased regularly, such as foodstuffs and toiletries. The results show that the limited rationality and interactions of each agent drive the unique behaviour of the system, and that each pricing strategy has a different impact on retailer profit and market share. This study provides insights into pricing decision strategies related to price promotion.

Two-Stage Pricing Decision for Low-Carbon Products Based on Consumer Strategic Behaviour

The development of information technology has changed the pricing strategy of retailers, and consumers have also made strategic consumption behaviours accordingly. At the same time, changes in the environment have caused changes in the retailer’s products and raised consumers’ environmental awareness. This paper uses a two-stage pricing model to study the low-carbon product pricing decisions of retailers based on strategic consumers with low-carbon preferences in two situations. Through the analysis of low-carbon and ordinary products in two situations, the following conclusions can be drawn: (1) In a market where retailers only sell low-carbon products, product prices and profits increase as consumers’ green preference θ increases. (2) In the low-carbon product and ordinary product markets, the price and profit of low-carbon products increase with regard to consumers’ green preference θ . (3) In the second stage, when consumers’ intertemporal discount factor β for ordinary products is larger than that of low-carbon products, the retailer’s total profit is smaller. The research conclusion comprehensively analyses the impact of customer strategic behaviour on the two-stage pricing decision of green differentiated products, which provides a very important reference for retailers to make pricing optimization decisions.

Retail Electricity Pricing Strategy via an Artificial Neural Network-Based Demand Response Model of an Energy Storage System

The distribution company (DISCO) determines optimal retail prices to operate the distribution network efficiently while promoting demand response (DR) programs. In addition, an energy storage system (ESS), which improves peak load management, is widely used for price-based DR. This paper proposes an electricity retail pricing strategy that considers the optimal operation of an ESS using a machine learning algorithm. An artificial neural network (ANN) is used to develop a practical model of the DR scheduling of an ESS. This model is trained using historical data that include the electricity price and the corresponding optimal demand obtained from the building energy management system. The proposed model is replicated using mathematical equations and directly integrated into the constraints of the retail pricing optimization problem of the distribution management system. The proposed ANN-based DR model of the ESS allows the development of an optimal pricing strategy with a single-level structure while reflecting the decision-making process of both the DISCO and the building operator. The proposed ANN-based DR model is verified through case studies, which prove that the model successfully expresses the price-optimal demand function and has high practical applicability. The results of the retail pricing demonstrate that the proposed strategy can accurately determine the balancing points while reducing the peak load.

Optimal channel decision of retailers in the dual-channel supply chain considering consumer preference for delivery lead time

Facing competition from manufacturers' online direct channels, how retailers make sales channel decisions to increase consumer stickiness has become the core concern of the industry and academia. Empirical research showed that delivery lead time is a key factor that affects consumers' preference for online channels. To analyze the impact of consumer delivery time preference on channel selection and pricing strategy of retailers, consumer delivery lead time preference function was improved from a linear function to an exponential function and consumer demand under the mixed dual-channel supply chain of manufacturer and retailer was derived. Then, the Stackelberg game models under different channel strategies of retailer were established and solved. Results show that consumer preference for delivery lead time has four implications on the channel decision of retailers under manufacturer encroachment in the dual-channel supply chain. First, the dual retail channels strategy is the optimal choice for retailers, and the profit margins that a retailer obtains from dual retail channels supply chain and single online retail channel supply chain will increase as consumers' delivery lead time preference coefficient increases. Second, the optimal pricing of online retail channel and offline retail channel is positively related to consumers' delivery lead time preference coefficient. By contrast, the optimal pricing of online direct channel is negatively related to consumers' delivery lead time preference coefficient. Third, the optimal pricing of online retail channel is higher than that of offline retail and online direct channels. Fourth, a retailer and a manufacturer can adopt a compensation-based whole price contract to address the conflict brought about by the optimal channel choice of the retailer. This study introduces consumer delivery lead time preference into retailer channel decision making and provides a theoretical reference for retailer's mixed channel construction in practice.

Pricing and return strategy of online retailers based on return insurance

With the development of e-commerce, online shopping has become increasingly common, and as a result, consumers inevitably encounter the problem of returns. Therefore, pricing, return policy and return insurance strategy have attracted considerable research attention. In this paper, we construct four models to study pricing, return policy and return insurance strategy. We show that when a product's net residual value is greater than or equal to zero, online retailers should offer a money-back guarantee (MBG) return policy; however, they do not have to offer free return insurance because the latter does not increase their market share and profit, nor does it increase consumer surplus. The optimal strategy of insurance providers is unaffected by whether the policyholder is an online retailer or a consumer and should be neutral, which helps insurance providers gain the trust of policyholders. Consumers should buy products only when online retailers offer an MBG return policy; however, consumers should not do so if the online retailer provides free return insurance.

Manufacturer - Retailer Pricing, Payment and Replenishment Strategies with Discount Dependent Credit Period for Price-Stock dependent demand

Manufacturer - Retailer Pricing, Payment and Replenishment Strategies with Discount Dependent Credit Period for Price-Stock dependent demand

Investigating the effects of demand flexibility on electricity retailers’ business through a tri‐level optimisation model

The investigation of the effects of demand flexibility on the pricing strategies and the profits of electricity retailers has recently emerged as a highly interesting research area. However, the state-of-the-art, bi-level optimisation modelling approach makes the unrealistic assumption that retailers treat wholesale market prices as exogenous, fixed parameters. This study proposes a tri-level optimisation model, which drops this assumption and represents the wholesale market clearing process endogenously, thus capturing the realistic implications of a retailer's pricing strategies and the resulting demand response on the wholesale market prices. The scope of the examined case studies is three-fold. First of all, they demonstrate the interactions between the retailer, the flexible consumers and the wholesale market and analyse the fundamental effects of the consumers’ time-shifting flexibility on the retailer's revenue from the consumers, its cost in the wholesale market and its overall profit. Furthermore, they analyse how these effects of demand flexibility depend on the retailer's relative size in the market and the strictness of the regulatory framework. Finally, they highlight the added value of the proposed tri-level model by comparing its outcomes against the state-of-the-art bi-level modelling approach.