Optimal Pricing Strategy Research Articles

Optimal Pricing Strategy in an Unreliable M/M/1 Retrial Queue with Delayed Repair and Breakdown Deterioration

Optimal Pricing Strategy in an Unreliable M/M/1 Retrial Queue with Delayed Repair and Breakdown Deterioration

The Impacts of Payment Schemes and Carbon Emission Policies on Replenishment and Pricing Decisions for Perishable Products in a Supply Chain

In the supplier–retailer–consumer system, the retailer’s replenishment and pricing strategies impact the entire transaction process, forming a comprehensive trading market. Suppliers offer advance-cash-credit payments to retailers, while retailers provide customers with cash-credit payment options. In the current health-conscious consumer market, purchasing decisions are influenced not only by commodity prices but also by the freshness of products, particularly perishable goods. Growing awareness of climate change and the advent of carbon emission policies have raised concerns about the environmental costs of business transactions. This study focuses on perishable products whose demand is influenced by both price and freshness. It explores the adoption of various payment methods by suppliers and retailers, as well as the impact of carbon emission cap-and-trade policies or carbon tax policies on management and pricing strategies. Suitable inventory models are established to determine the optimal replenishment and pricing strategies for maximizing the current value of total profit. We illustrate that the current value of total profit demonstrates joint concavity concerning both the selling price and the replenishment time. Finally, we verify the proposed models using numerical examples and present the findings of sensitivity analyses. The findings of this study yield several valuable insights for inventory management of perishable goods.

Research on automatic pricing and replenishment decision of vegetable commodities based on optimization model

In fresh food superstores, because vegetable commodities are characterized by perishability and high value loss, superstores usually replenish daily commodities based on the historical sales and demand of various commodities. In order to make the optimal replenishment decision, this paper firstly firstly uses Matlab fitting toolbox to get the functional relationship between the total sales volume and the cost-plus pricing, so as to analyze the relationship between the total sales volume and the cost-plus pricing of each vegetable category, and then takes the category as a unit, and then constructs the optimization model, and solves the optimal replenishment volume and pricing strategy. The replenishment decision is obtained by filtering out the most profitable single product among the factors of unit price, sales volume, and total replenishment volume through objective planning under the constraints of considering the single product category and minimum display volume.

Optimal pricing strategy in the closed-loop supply chain using game theory under government subsidy scenario: A case study

Automotive battery production always receives government supports which directly affect the recycling of used products collected from secondary markets. Accordingly, an optimal product pricing strategy and efficient policy suggestions must be provided for this industry. This study used Stackelberg models to analyze three categories of pricing strategies related to the recycling process of car batteries when government subsidy is paid. These models are applied to make optimal decisions in two centralized and decentralized modes to investigate the links between and influences of different parameters of the problem on one another. Finally, a numerical example based on a real case study in Iran is applied to the models. The results indicate that making centralized decisions leads to a higher level of profitability than decentralized decision-making in the under-study industry. Accordingly, maintaining coordination and integration among the supply chain components in the decision-making process increases the profitability of the entire network.

Bundling products and service on influencer channels

This study investigates the optimal service pricing strategies for manufacturers within the burgeoning field of influencer live-streaming marketing. By examining a dynamic where manufacturers collaborate with social media influencers, the research evaluates the efficacy of bundling products and services versus separate pricing under varying conditions. The study uncovers that the gap between the two service pricing models will increase as the service cost increases. Moreover, the lower the service cost, the more obvious the relative advantage of the bundling model. That is, bundling is most beneficial when service costs are low, whereas separate pricing becomes advantageous as service costs escalate. In addition, the decrease in the rate of product defects can lead to an increase in the relative advantage of the bundling model. Intriguingly, the optimal promotional approach for influencers shifts in response to these pricing strategies, favoring a combined product-service promotion when services are priced separately. The study further reveals a direct correlation between product defect rates and profitability, especially under separate pricing scenarios. These insights offer valuable guidance for manufacturers and influencers in strategizing their offerings and promotions in the digital marketplace.

Reference Dependence in Queue Design and Pricing Strategies

This research investigates the effect of reference dependence on waiting times in service systems which formerly used a first-in-first-out (FIFO) service but have introduced a priority line with a fee. Our model combines reference-dependent gain-loss utility with standard customer utility, and we posit that customers are pleased with shorter-than-expected waiting times, whereas longer-than-expected times lead to dissatisfaction and an increased likelihood of balking. The study explores two scenarios: a captive customer system (CCS) and a noncaptive customer system (NCCS), with a focus on optimal pricing and segmentation strategies for revenue and social welfare maximization. The results reveal that, in a CCS, the service provider should implement observed and unobserved customer segmentation to optimize revenue and social welfare, respectively. In an NCCS, the impact of customer segmentation on revenue maximization depends on the value of regular customers, their loss reference-dependent preferences, and the system’s offered load. Alternatively, if the service provider seeks to maximize social welfare, the provider’s use of customer segmentation relies solely on the system’s offered load and customers’ reference-dependent preferences. Our findings also indicate that reference dependence can have varying impacts under different conditions, suggesting the effectiveness of tailored service and pricing strategies. Notably, a CCS generates more revenue than does an NCCS because of its captive nature, and, surprisingly, increasing the service rate can decrease revenue while improving social welfare. These insights have significant implications for service management strategies for a CCS and an NCCS. Funding: J. Liu was supported by the National Natural Science Foundation of China (General Program) [Grant 72071112]. J. Chen was supported by the National Natural Science Foundation of China (Major Program) [Grant 71490723]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/serv.2023.0033 .

A Literature Review on Pricing Decisions for Complementary Supply Chains Considering Social Preference Behavior

In practice, many enterprises have achieved better market results through the implementation and continuous optimization of the complementary products strategy. Although complementary products can bring higher value and utility to customers' consumption experience, thus affecting the production operation and sales price decisions of enterprises, the strategic choices of complementary supply chain members will be affected when facing the different social preference behaviors of the members in the complementary supply chain and the complex supply chain structure. Based on this, this paper considers the vertical altruistic preference of the manufacturer over the retailer and the horizontal altruistic preference of the manufacturer over the manufacturer of the complementary product under different altruistic preference dimensions for a two-level supply chain system consisting of two manufacturers producing complementary products and a common retailer, and analyzes the optimal pricing strategies of supply chain members under different altruistic preference levels, which is of great significance for the stable operation of the supply chain.

To Skim or not to Skim: Studying the Optimal Pricing Strategy for Technology Products

Pricing of technology products often follows a skimming strategy in which a firm charges the highest price at product launch then reduces the price over time to attract additional buyers. Price-skimming has not been adequately examined in the literature related to technology products. Most pricing models proposed in the literature consider only initial product purchases while ignoring repeat purchases. However, for technology products, frequent upgrades often result in substantial repeat purchases. To fill this void, we develop an optimization model that accounts for both initial and repeat purchases. We find that the effectiveness of price skimming is highly dependent on the rate of repeat purchases. When the repeat purchase rate is low, firms may be better off delaying price reduction to accumulate more profit earlier in the product lifecycle, thus compensating for the decline in sales that occurs later in the lifecycle. For example, price skimming may not be the optimal pricing strategy for fad products with low repeat-purchase rates due to the product losing popularity in a short time period. Furthermore, contrary to common expectations, in markets highly sensitive to price changes firms may get away with charging a higher introductory price but must decrease the price over time to motivate sales.

Subscription Pricing for Free Delivery Services

Many firms that offer home delivery of products purchased online now provide consumers the option of subscribing to a membership plan for free delivery of limited or unlimited number of orders instead of customers paying delivery charges for each order. This paper seeks to understand the benefits to firms and consumers of introducing such free-delivery subscription (FDS) plans to complement their traditional pay-for-delivery (PFD) option, characterize the firm's optimal FDS subscription pricing strategy, and study the effects of product, consumer, and market characteristics on the subscription fees and firm's profits. We develop and analyze an economic model that incorporates salient features of product delivery settings that prior models of subscription pricing do not fully capture. The features include simultaneous availability of PFD and FDS options, lift in a consumer's demand when she switches from PFD to FDS, the possibility of attracting new consumers when the firm introduces FDS, and order batching by customers due to per-order delivery charges and free-delivery order allowances. Our utility-based approach to model consumers’ purchasing choices incorporates consumer heterogeneity both in terms of their utility for the product and their shopping preference under the PFD option. For homogeneous consumers, we show that introducing a FDS plan raises the firm's profit, establish the optimality of offering unlimited free-delivery allowance, and analyze comparative statics. With multiple customer types, our analysis of two subscription pricing strategies for FDS plans—a single “Universal” plan and multiple “Tiered” plans with varying subscription fees and free-delivery limits—leads to several interesting insights on delivery pricing strategies, as well as drivers and sensitivity of the optimal policy, profits, and number of subscribers. We supplement this analysis with extensive computational experiments that reveal a substantial increase in profits when a firm adds one or more FDS plans to its PFD option even though the optimal subscription fee(s) only covers part of the firm's actual shipping costs. These results also permit us to gauge the influence and understand the trends in the profitability of the Universal and Tiered plans as various parameters change.

Optimal bidding strategy for integrated CHP system by modified heuristic algorithm considering CO2 emission in energy and reserve markets

Purpose This study aims to solve optimal pricing and power bidding strategy problem for integrated combined heat and power (CHP) system by using a modified heuristic optimization algorithm. Design/methodology/approach In electricity markets, generation companies compete according to their bidding parameters; therefore, optimal pricing and bidding strategy are solved. Recently, CHP units are significantly operated by generation companies to meet power and heat, simultaneously. Findings For validation, it is shown that profit is improved by 0.04%–48.02% for single and 0.02%–31.30% for double-sided auctions. As heat price curve is extracted, the simulation results show that when CHP system is integrated with other units results in profit increase and emission decrease by 3.04%–3.18% and 2.23%–4.13%, respectively. Also, CHP units significantly affect bidding parameters. Originality/value The novelties are pricing and bidding strategy of integrated CHP system is solved; local heat selling is considered in pricing and bidding strategy problem and heat price curve is extracted; the effects of CHP utilization on bidding parameters are investigated; a modified heuristic and deterministic optimization algorithm is presented.

Retraction Note: the optimal pricing strategy to evaluate the reputations of sellers in online platforms using the game theory model

Retraction Note: the optimal pricing strategy to evaluate the reputations of sellers in online platforms using the game theory model

Integrated Departure Time and Parking Location Choices in a Morning Commute Problem under a Partially Automated Environment

This study formulates the joint decisions of commuters on departure time and parking location choices in a morning commute problem where the commuters travel with autonomous vehicles (AVs) or human-driven vehicles (HVs). Under a mixed traffic environment, we aim to explore the impacts of parking capacity and parking pricing on the equilibrium travel pattern and the system performance. We build a dynamic equilibrium model for the morning commute problem by assuming that the parking slots can be grouped into central and peripheral clusters based on the distance between the parking location and the workplace. We first analyze the parking location preferences of commuters towards the two parking clusters under a mixed traffic environment. We then examine the equilibrium conditions and identify all the equilibrium travel patterns. We further analyze the system performance measured by the total travel cost with respect to the parking prices and the capacity of the central cluster. The optimal parking pricing scheme is also derived to minimize the total travel cost. We conduct numerical analysis to demonstrate the change in the total travel cost against the parking capacity of the central cluster and its parking price. Sensitivity analysis is performed to show the impacts of the network configuration on the total travel cost.

Quality disclosure strategy in a competitive environment with consumers' homogeneity and heterogeneity

This study examines the optimal pricing and disclosure strategies of sellers who possess private quality information. We consider two market structures, namely, monopoly market and duopoly market; under each market structure, we further consider two characteristics of consumer preferences for the same product: homogeneity and heterogeneity. How competition and whether consumers are heterogeneous affects sellers' disclosure strategies, and profitability is the focus of our attention. Interestingly, we show that the monopolistic seller's profit is likely to increase as the disclosure cost, which is not possible in a competitive environment. We indicate that when consumers are homogeneous, sellers can obtain higher returns and are more likely to engage in quality disclosure. Finally, we show that when the market is filled with homogeneous consumers, competition always increases the motivation for sellers to engage in quality disclosure. However, when the market is filled with heterogeneous consumers, competition actually hinders sellers from engaging in quality disclosure when the cost of disclosure is low. Our results help company managers in making better disclosure and pricing strategies.

Optimization of replenishment and sales strategy of vegetable products based on ARIMA time series model and combination sales

Due to the short shelf life of vegetable items, supermarkets usually restock daily based on the historical sales and demand of each item. In order to develop an optimal strategy for replenishment and sales of vegetable items, this study firstly predicted the total daily replenishment in the coming week using ARIMA time series model, and then this study took the hypermarket revenue as the objective function and considered the correlation between vegetable categories in the sales data, and adopted a combination sales strategy to increase the sales volume. This study establishes the combination sales formula, and uses the third-party library function combined with the genetic algorithm to obtain the optimal coefficient combination to maximize the superstore's revenue, and finally constructs the optimization model of pricing strategy for each category of vegetables, and solves the optimal pricing strategy, and ultimately obtains the daily replenishment of total amount of various categories of vegetables in the coming week.

Replenishment And Automatic Pricing Strategy for Vegetable Products Based on Genetic Algorithm

In order to improve the accuracy of replenishment and pricing of vegetable commodities sold in supermarkets, and to maximise the benefits of vegetable commodities sold in supermarkets, this paper comprehensively establishes a strategic planning model for replenishment and automatic pricing of supermarkets. Firstly, we carry out descriptive statistical analysis and non-linear fitting on the historical sales data of supermarkets to find the distribution pattern of the sales of each single product of vegetables, and then find out the relationship between each single product of vegetables through correlation analysis. and then find out the relationship between each vegetable item through correlation analysis. After that, we built an LSTM time series forecasting model based on the cost data to predict the replenishment volume of the six vegetable categories in the coming week. Finally, in order to maximise the revenue of the superstore, we constructed a pricing planning model for the combination of vegetable categories, and solved the optimal purchase quantity and pricing strategy based on genetic algorithm.

Research on Nash Equilibrium of Dual-Channel Supply Chain Based on Wholesale Price Discrimination and Sales Efforts

The progress of communication technology and the Internet has made the dual-channel supply chain have great development. Supply chain members have to compete and cooperate with other enterprises on the chain in order to obtain greater self-benefit. In the competitive-cooperative relationship among enterprises, price discrimination and sales effort are common tools of operation, and Nash equilibrium theory is a common strategy in the process of supply chain game. Whether manufacturers can promote retailers to implement sales efforts through price discrimination and ensure that the overall revenue of the supply chain is improved at the Nash equilibrium is great significance to both the supply chain and individual enterprises. This paper constructs a decentralized dual-channel supply chain mathematical model composed of an independent manufacturer, an offline retailer, and an online retailer, taking into account the impact of the offline retailer’s sales efforts on his demand and its positive external for the other channel. The revenue matrix of retailers’ decisions about whether or not to pay their sales efforts is built under the condition that manufacturers charge different wholesale prices to different retailers and solves the condition of every decision combination becoming the Nash equilibrium using the Nash equilibrium game theory. Finally, the optimal pricing strategy of the manufacturers is analysed to get the constraints of this dual-channel supply chain achieving Pareto improvement when manufacturer uses wholesale price discrimination strategy.

Optimal pricing strategies for distribution system operator in coupled power-transportation system

The power grid and transportation network are coupled by the charging behavior of electric vehicles. Based on the coupled power-transportation network model, this paper first analyzes the effect of the distribution system operator’s (DSO) electricity selling price on guiding the charging behavior of electric vehicles in the transportation network and then builds the DSO’s optimal pricing formulation. Considering the competition between multiple charging network operators (CNOs), this paper establishes a game model between CNOs and solves it iteratively through the best response dynamic method. An approximation method using the elasticity matrix is proposed to speed up the solution by reducing the multi-layer optimization to a single layer one in each iteration, with its effectiveness validated through numerical tests. Furthermore, the paper discusses the issue of the prisoner’s dilemma that arises among CNOs and explores the potential impact of their cooperative strategies on the overall system.

A study on the application of game theory modeling in the analysis of pharmaceutical price elasticity

Abstract Setting reasonable drug prices is the fundamental goal of drug price elasticity analysis, and the game theory method can play a role in drug pricing by analyzing the behaviors of multiple game subjects to give a plan that meets the best interests of all parties. The optimal pricing strategies under different threshold conditions are summarized by establishing four model assumptions and solving them based on the basic model of game theory and the bidding process. Accordingly, the drug pricing of Pharmaceutical Company F was analyzed, and it was found that its optimal pricing was 21.3yuan, at which time the profit was 132.74% higher than the original pricing profit. After applying this pricing, it was found that the implementation of the new pricing increased the mean score of the company’s profitability by 0.16738 to 0.19504 as compared to before the optimized drug pricing strategy, indicating that the pricing strategy improved by the game theory model is able to provide the company’s level of profitability and is feasible.

Research on low-carbon closed-loop supply chain strategy based on differential games-dynamic optimization analysis of new and remanufactured products

<p>With the current increasing global demand for low-carbon and environmentally friendly products, promoting the sustainability of closed-loop supply chains has become one of the key measures. However, consumers often do not regard remanufactured products as equivalent to new products. Therefore, this paper proposes a dynamic closed-loop supply chain that incorporates consumers' purchasing preferences to model a long-term game with product differentiation. Moreover, to enhance consumer acceptance of remanufactured products and reduce manufacturers' costs, low-carbon technologies and cost-sharing mechanisms are introduced. In this way, we construct a differential game in which the manufacturer sells new and remanufactured products through a retailer and makes decisions about the level of low-carbon technology in the remanufacturing process. Based on the theory of differential games, this paper analyzes three different power structures: the manufacturer-dominated Stackelberg game, the Nash game, and the retailer-dominated Stackelberg game. The optimal low-carbon technology level and pricing strategy are obtained by applying Pontryagin's maximum principle. The study shows that the retailer-led Stackelberg game helps retailers maximize profits, while the Nash game enables the entire closed-loop supply chain system to achieve the highest overall profits. This paper innovatively integrates low-carbon technologies into the dynamic game model of the remanufacturing process and reveals how the game behavior of supply chain participants affects the application of low-carbon technologies and the overall profit of the supply chain by comparing the cost-sharing mechanisms under different power structures. The results provide important theoretical support and practical references for closed-loop supply chain management with product differentiation.</p>

A Game-Theory-Based Contract Mechanism to Facilitate Technology Spillover in Emerging Electric Vehicle Markets

Electric vehicles (EVs) have been increasingly adopted by both developing and developed countries as an effective means to cope with energy shortage and provide environmental-friendly transportation solutions. However, due to technology gap, domestic electric vehicles (DEVs) in developing countries often cannot compete with well-established imported electric vehicles (IEVs) from developed countries. Therefore, developing countries often face the dilemma of increasing the EV adoption through more IEVs and promoting the development of DEVs. This article proposes an incentive-compatible contract mechanism to address this dilemma. Through a set of game theory models, we compare the commonly used subsidy and tariff policies against the spillover effect of a technology assistance program (TAP) and derive the optimal pricing strategies for DEVs and IEVs. The results show that the implementation of TAP can lead to a more competitive market and significantly increase social welfare. Consumers can benefit from reduced prices of both the DEVs and IEVs, while the profits of the IEVs and DEVs can be enhanced at varying degrees of technology spillover resulted from TAP. Therefore, the proposed TAP mechanism effectively complements the existing subsidy and tariff policies and provides a viable instrument for the government of developing country to reconcile the existing policy dilemma.