Optimal Retail Price Research Articles

Pricing Decisions in Dual-Channel Supply Chains Considering the Offline Channel Preference and Service Level

With the rapid development of e-commerce, the online channels encroaching on the offline sales market are becoming more serious, which will definitely harm the offline market. Moreover, there exists a certain percentage of consumers (mostly elderly people) who are not able to purchase online because they lack digital skills. Therefore, understanding the impact of the purchase channel preference and service level on pricing decisions is vital for the dual-channel supply chain management. Focusing on the channel preference and service level, we first develop an optimal pricing model containing centralized and decentralized decision-making for an online and offline retailer by deploying the Stackelberg game. We first develop a Stackleberg game to capture such a dual-channel supply chain with the offline channel preference and service level. Secondly, under centralized decision-making, we derive the optimal retail prices and obtain the optimal total profit. Thirdly, under decentralized decision-making, we obtain the optimal retail prices and optimal total profit as well. Moreover, extensive monotonicity properties when system parameters change are obtained. Relying on the theoretical results, firstly, we show that the improvement of the offline service level would lead to higher pricing of the commodities for both online and offline channels. From our numerical results, when the service level is improved, the offline and online optimal pricing increases by 47.5% and 31.1%, respectively, which may contradict the conventional belief that the improvement of one channel would harm another one. Secondly, we demonstrate that the benefit of improving the offline service level has a diminishing marginal effect. The numerical results show that when the current service level is low, the effectives of improving the service level is roughly five times that when the service level is high. This indicates that the investment in improving the offline service level should not be unlimited. Thirdly, we show that the pricing decision under centralized decision-making should be adopted with the existence of both the offline channel preference and offline service.

Analysis of Optimal Variables of Return Freight Insurance Decision for Each Part of Supply Chain Based On Stackelberg Game

Based on the theory of demand and profit function, this paper studies the effects of different return freight insurance policies on manufacturers (sellers), platform optimal price, and optimal wholesale price under the distribution model. By constructing a mathematical model under Steinkelberg game, this paper analyzes the model without freight insurance and the model with freight insurance borne by different parts of the supply chain to explore the changes of the optimal variables of each party. The results show that: with the increase of the residual value of returned goods, the optimal retail price and the optimal return volume will increase, while the optimal wholesale price and the optimal demand will decrease. Under the model of freight insurance shared by the platform and the manufacturer, with the increase of freight insurance shared by the manufacturer and the platform, the optimal selling price increases, the optimal demand and the optimal return volume decrease, and when the cost of freight insurance borne by the manufacturer exceeds half, the wholesale price increases. Under the model of buyer bearing freight insurance, when consumers have high price sensitivity, the higher the cost of consumer bearing freight insurance, the lower the maximum selling price.

Fresh Produce Ordering, Pricing and Freshness-Keeping Decisions with Call Option Contracts and Spot Markets

Considering the characteristics of both quality and quantity losses in fresh produce as well as the existence of spot markets, optimal retailer ordering, pricing, and freshness-keeping decisions through the single ordering policy (firm ordering only or option ordering only) and the mixed ordering policy (firm ordering and option ordering simultaneously) are constructed based on option contracts and analyzed for the retailer under different ordering policies. The results show that there is a unique optimal pricing, ordering, and freshness-keeping decision under all three ordering policies, but there is no joint decision. The optimal freshness-keeping and retail price under the mixed ordering policy are lower than those under the option ordering only but higher than those under the firm ordering only. When only a single order can be placed, the retailer’s optimal ordering policy is determined by demand risk. When all three ordering policies are available, the optimal ordering policy for the retailer is the mixed ordering policy. A spot market will weaken the role of option contracts in mitigating supply chain risks, and the larger the risk, the more significant the role of the spot market.

Decision making in fuzzy closed loop dual channel supply chain

This paper discusses the optimal pricing and collecting decisions in a fuzzy environment of the three closed-loop dual-channel supply chain models where a manufacturer produces the original product from fresh materials and unfashionable products. The manufacturer sells the original products to the customers using direct and retail channels (forward dual channel). In the reverse channel, the manufacturer, third-party collector and retailer individually take responsibility for unfashionable products acquired from the market in the three models. Remanufacturing cost, product collecting cost and market demand are treated as fuzzy variables. The optimal decisions wholesale price, direct price, retail price and collection rate are derived using fuzzy set theory and game theory approach in the three decision models. Finally, numerical illustrations clarify the impact of the fuzzy degree parameters on the decision variables and the expected profits of the players. It is found that the manufacturer decision model is superior for receiving the maximum expected profits of the players and also being more convenient from the customer?s perspective.

Supply Chain Resilience Enhancement Strategies in the Context of Supply Disruptions, Demand Surges, and Time Sensitivity

Supply chain disruptions, including trade disputes, regional conflicts, and the COVID-19 pandemic, have highlighted the importance of supply chain resilience. This study focuses on investment decisions related to supply chain resilience, including considerations of supply disruptions, demand disruptions, and demand time sensitivity. The study uses a Stackelberg game model, with the retailer as the leader and the supplier as the follower, to analyze and compare optimal strategies for supply chain participants under different levels of risk. The results show that the severity of risk events impacts the optimal retail price, optimal wholesale price, supply chain recovery time, and expected profits for each participant. The investment in supply capacity enhancement not only expands the ability to meet demand but also encourages suppliers to expedite supply chain recovery, elevate demand fulfillment rates, and enhance the overall return on investment in supply chain resilience. As a result, the resilience of the entire supply chain is fortified. Similarly, it has been found that centralized decision-making leads to lower prices, shorter recovery times and greater supply chain resilience than decentralized decision-making. This study offers theoretical underpinning for corporations to effectively address risky occurrences, ensure supply security, enhance supply chain resilience, and imparts support for governments involved in humanitarian relief efforts.

Optimal pricing strategies of e‐commerce supply chain considering consumers’ anticipated regrets under the background of blockchain anti‐counterfeiting technology

AbstractIn this study, we investigate pricing decisions with different decision sequences in an e‐commerce supply chain. The e‐commerce platform sells blockchain‐compatible products through a self‐operated model, while the retailer operating on the platform sells general products. Furthermore, we take into account the impact of counterfeits infiltrating the general product market. This can trigger consumers’ anticipated regrets, including high‐price regret and fake purchase regret. We design three scenarios: Scenario ES (the e‐commerce platform makes the decision first), Scenario RS (the retailer makes the decision first), and Scenario VN (they make decisions simultaneously). We study the impact of consumers’ anticipated regrets and the decision sequence on pricing strategies, as well as the profits of the e‐commerce platform and the retailer. Our results show that the optimal retail prices of the two versions of the products and the profits of the e‐commerce platform and the retailer are negatively correlated with the relative regret intensity. The profits of the e‐commerce platform and the retailer are the lowest under Scenario VN due to the fiercest competition. The e‐commerce platform prefers Scenario RS to Scenario ES. If the counterfeit penetration rate is small and the commission rate is large, the retailer prefers Scenario RS to Scenario ES. However, if the counterfeit penetration rate is high, or if both the counterfeit penetration rate and the commission rate are low, the retailer prefers Scenario ES to Scenario RS. Furthermore, if government penalties (or consumer claims) exist, the retailer should combat counterfeiting appropriately for better financial performance.

Research on Supply Chain Pricing Strategies under Carbon Emission Quota Constraints

In order to reduce the carbon emissions of manufacturers and retailers in their business activities, carbon emission limits must be set for manufacturers and retailers respectively, and they must make favorable decisions within the limits. This paper will focus on a two-level supply chain system composed of a single manufacturer and a single retailer, and explore the optimal wholesale price, optimal retail price, and optimal profit under four scenarios: neither is constrained by carbon quotas, only the manufacturer is constrained by carbon quotas, only the retailer is constrained by carbon quotas, and both are constrained by carbon quotas, by constructing Lagrange functions. Comparative analysis will be conducted. Research has shown that only when manufacturers are subject to carbon quotas, the optimal wholesale and retail prices will rise, and the optimal profits of both manufacturers and retailers will decrease; When retailers are constrained by carbon quotas, whether manufacturers are constrained by carbon quotas does not affect the optimal price and profit; When both are subject to carbon emission restrictions and retailers increase their carbon emission quotas, manufacturers will lower wholesale prices and retailers will lower retail prices.

Choice of the co-opetition model for a new energy vehicle supply chain under government subsidies

We study the co-opetition model selection problem for a new energy vehicle (NEV) supply chain comprising a dominant manufacturer and a subordinate supplier. Given the impact of R&D subsidies on suppliers’ technological innovation, we consider two co-opetition models, namely wholesale co-opetition and patent licensing co-opetition, derive the optimal decisions of the models, and analyze the optimal selections for supply chain members. We also conduct extensive numerical studies to verify the research findings and generate practical insights. We find that patent licensing co-opetition is not necessarily beneficial to supply chain members. However, under certain conditions, patent licensing co-opetition can create a “win-win” situation for the supply chain. Furthermore, as the degree of product substitution increases under patent licensing co-opetition, the optimal retail prices of the manufacturer and supplier both decrease first and then increase, but their thresholds are different. In addition, the R&D cost coefficient positively affects the fixed cost of patent usage, but it does not affect the unit patent licensing fee. This study provides theoretical guidance for supply chain members to choose the optimal co-opetition models and has important practical significance for promoting the sustainable development of the NEV industry.

Developing Platform Supply Chain Contract Coordination and a Numerical Analysis Considering Fresh-Keeping Services

With changes in demand and the emergence of new distribution channels, consumer-centric buyer’s markets for many products have been formed. The platform supply chain has been continuously optimized and upgraded. Supply chain leaders have moved downstream to the end of the supply chain. The operational value has been further enhanced. The corresponding systematic construction of the platform supply chain has become an important driving force for future development. The model in this paper is different from the traditional supply chain contract model, which mainly focuses on suppliers or demand. In order to meet the requirements of fresh-keeping services and the goal of revenue sharing, we integrate the production and circulation characteristics of fresh produce into the design of a contract model. In this paper, a revenue-sharing contract model of the fresh produce supply chain is constructed based on the core position of retailers, the uncertainty of the market size, and the consideration of a fresh-keeping service. The model is mainly composed of the core retailer and the supplier. Through further numerical analysis, we verify the effectiveness of the revenue-sharing contract model in supply chain coordination. We also analyze the change trends in the optimal retail price, optimal freshness level, and optimal order quantity caused by changes in both the fresh-keeping service capacity and the revenue-sharing coefficient. The results show that after changing these two parameters, the supply chain can achieve coordination under the specified parameter values. The changed parameters will also lead to certain change trends in the optimal retail price, optimal freshness level, and optimal order quantity, and will have a corresponding impact on the stability of supply chain operation. This research provides a relevant theoretical and empirical basis for a fresh produce supply chain contract model with retailers at the core position. We also provide guidance and reference for optimizing the supply chain management mode and improving the overall operational efficiency of the fresh produce supply chain.

Pricing decisions of risk averse logistic companies with carbon cap and trade under Stackelberg game.

With the implementation of the double carbon plan, this paper considers the delivery fees of two risk averse logistics companies under carbon cap and trade mechanism. We establish logistics company Stackelberg (MS) model and retailer Stackelberg (RS) model under mean variance (MV) framework, respectively. We obtain the optimal delivery fees and retail prices. We find out that the higher degree of risk aversion can lead to a lower delivery fee. We also show that a higher carbon trading price or a higher cross price sensitivity will increase delivery fees. Moreover, we indicate that the performances of logistics companies under MS scenario are higher than that RS scenario. In addition, we suggest that under the carbon cap and trade rules, in order to obtain higher profits, logistics companies should use fuel vehicle for transportation under certain conditions, and use electric vehicle in other cases.

Mid‐Term Bidding Strategy for an Energy Internet Zone Based on Distributionally Robust Optimization

Energy internet zones (EIZ) supply multiple energy carriers to customers in certain regions. They can achieve high energy efficiency by energy cascade utilization. In mid‐term, they participate in the wholesale market and retail market simultaneously. Customers can shift their energy use among different hours and energy carriers to satisfy demand according to the retail prices. Unfortunately, multiple energy systems and markets bring various uncertainties on demand and prices. In this paper, the weekly bidding strategy for the EIZ is proposed to determine the optimal bilateral contracts to sign and the optimal energy retail prices. In retail market, the satisfaction degree and elasticity matrix describe customers' response. Distributionally robust optimization is adopted to consider the distributional uncertainties of random variables and Worst‐case Conditional Value‐at‐Risk is employed for risk management. The distributional uncertainties of pool prices and elasticity matrix are discussed in this paper. An EIZ in Shanghai, China is adopted to illustrate the proposed strategy. The results have great resistance to distributional uncertainties. The risk aversion and satisfaction degree affect the EIZ's strategy in wholesale market and retail market, respectively. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

A game theoretic framework for post-consumer recycled and new packaging industries

This paper presents a game-theoretic framework of competition for two packaging companies. The first one is a traditional packaging firm that employs new raw materials in its packaging and invests in innovative packaging solutions. In contrast, the other takes advantage of a combination of new and post-consumer-recycled (PCR) material based on a cost saving strategy. The model incorporates the price and quality of the product as well as its packaging and is implemented on packaging firms with the same source of manufacturer/importer. Two different scenarios are considered with the potential to push companies towards sustainable solutions; namely the existence of eco-conscious consumers and government tax on the new raw material packaging. The problem is established as a two-stage game, and the optimal level of investment in packaging innovation, the optimal ratio of PCR material and the optimal retail prices are derived, all in equilibrium. A real-world example and also parametric and sensitivity analysis are provided and valuable insights are derived. The results indicate that current proposed virgin tax plans do not provide a strong incentive towards sustainable packaging, whereas eco-conscious customers give this impetus. It was also observed that the imposed virgin tax does not impede innovation investment in virgin packaging companies.

Optimizing decisions for post‐harvest ripening agricultural produce supply chain management: a dynamic quality‐based model

AbstractFresh agricultural produce, which is characterized by post‐harvest ripening and is required for long‐term transportation in cross‐regional trade, is commonly harvested at the unripe stage and undergoes a routine process of natural ripening followed by senescence. A model based on the dynamic quality of post‐harvest ripening agricultural produce (PRAP) was proposed to optimize decisions to improve supply chain profits. To verify its effectiveness and robustness, the model is applied to a real banana supply chain. The theoretical derivations and simulation results show that, first, the optimal retail price and presentation timing based on the model can maximize the supply chain profit. Second, the proper choice of the combination of picking maturity and preservation temperature based on the time from picking to the retailer can effectively improve the on‐shelf quality and supply chain profit. Third, supply chain management strategies for PRAP and fully ripened agricultural produce should be developed based on the different quality change characteristics of these two produce types.

Operational decisions of low-carbon supply chains with triple bottom line under carbon tax policy

PurposeUnder the carbon tax policy, the authors examine the operational decisions of the low-carbon supply chain with the triple bottom line.Design/methodology/approachThis paper uses the Stackelberg game theory to obtain the optimal wholesale prices, retail prices, sales quantities and carbon emissions in different cases, and investigates the effect of the carbon tax policy.FindingsThis study’s main results are as follows: (1) the optimal retail price of the centralized supply chain is the lowest, while that of the decentralized supply chain where the manufacturer undertakes the carbon emission reduction (CER) responsibility and the corporate social responsibility (CSR) is the highest under certain conditions. (2) The sales quantity when the retailer undertakes the CER responsibility and the CSR is the largest. (3) The supply chain obtains the highest profits when the retailer undertakes the CER responsibility and the CSR. (4) The environmental performance impact decreases with the carbon tax.Practical implicationsThe results of this study can provide decision-making suggestions for low-carbon supply chains. Besides, this paper provides implications for the government to promote the low-carbon market.Originality/valueMost of the existing studies only consider economic responsibility and social responsibility or only consider economic responsibility and environmental responsibility. This paper is the first study that examines the operational decisions of low-carbon supply chains with the triple bottom line under the carbon tax policy.

Blockchain adoption or contingent sourcing? Advancing food supply chain resilience in the post-pandemic era

In the post-pandemic era, food supply chains and firms therein are facing unprecedented severe challenges, because once infection is detected, numerous products must be recalled or abandoned, and both suppliers and retailers in the supply chain suffer enormous loss. To survive under the pandemic, retailers have adopted different sourcing strategies, such as contingent sourcing, which, in turn, affect the upstream suppliers and hence the resilience of the whole supply chain. With the rapid development of digital technologies, retailers nowadays can utilize blockchain as a reliable and efficient way to reduce product risk and hence advance the resilience of food supply chains by improving product traceability and inspection accuracy, and making sourcing transparent. In this paper, we develop a game-theoretic model to investigate the interrelation between the retailer’s decisions on blockchain adoption and sourcing strategies. We consider that a retailer originally orders from a risky supplier while conducting an imperfect inspection to detect infected products before selling. The retailer may speculatively keep on ordering from the risky supplier or adopt contingent sourcing by ordering from an alternative safe supplier. The retailer also has an option to implement blockchain to improve the inspection accuracy and product traceability. We derive the optimal retail prices under different sourcing strategies with and without blockchain adoption and then analyze the incentives for sourcing strategy and blockchain adoption. Then, we identify the conditions of an all-win situation for food retailer, supplier, supply chain resilience, and consumers with/without government subsidy. Finally, we extend to consider the situation that some consumers have health-safety concerns and preferences for blockchain adoption.

Dynamic Optimal Decision Making of Innovative Products’ Remanufacturing Supply Chain

In order to realize the recyclability of innovative product resources, we explored the optimal dynamic path of each decision variable in the remanufacturing supply chain and analyzed the impact of each decision variable on supply chain performance. Based on the Bass innovation diffusion model, we established a remanufacturing supply chain model in which a single manufacturer leads and a single retailer follows, and the retailer is responsible for recycling. The optimal wholesale price, retail price, and recovery effort path were obtained through optimal control theory. We also discussed the influence of different innovation coefficients and imitation coefficients on the overall long-term profit of each member in the supply chain, and at the same time, found the optimal market share of the product. The research results show that the larger the market innovation coefficient and the imitation coefficient are, the larger the overall long-term profit of the manufacturer and the greater the market share of the product, while the overall long-term profit of the retailer and the entire supply chain will increase first and then decrease; when the innovation coefficient and imitation coefficient are above a certain level, retailers will not enter the market. In a market with a small innovation coefficient and a large imitation coefficient, the overall long-term profits of retailers and supply chains will be higher. This study provides a theoretical basis for the decision making of the remanufacturing supply chain of innovative products in a dynamic environment, and also provides guidance for the practice of nodal enterprises in the supply chain.

When can a manufacturer benefit from adding a direct sharing channel?

With the rapid development of sharing economy, the manufacturer has begun to establish direct sharing channels in addition to their existing distribution channels via independent retailers. Motivated by this business practice, this paper aims to answer the following questions: whether and when should a manufacturer establish a direct sharing channel? To this end, we first analyze a supply chain where a manufacturer distributes her product only through a retailer (the M-S Model), where we obtain the optimal retail price. Next, we consider the scenario where the manufacturer sets up a direct sharing channel in addition to the retail channel (the MR-S Model), where we obtain the optimal rental price and retail price. We then study the manufacturer's channel structure choice between the M-S and the MR-S models. Our main findings include the followings. First, the manufacturer may not always benefit from establishing a new sharing channel. The manufacturer will benefit only if the operating cost of sharing channel is low. However, when the operating cost of sharing channel is below a threshold, adding the sharing channel will decrease the profit at the retail channel, resulting in channel conflict. Second, only if the operating cost of sharing channel falls into a certain interval, the manufacturer's sharing channel will decrease the retailer's profit but increase the total supply chain profit. To avoid channel conflict, the two firms can adopt an appropriate sales reward contract so that both can benefit from the sharing channel. Lastly, when both the operating cost of sharing channel and the simultaneous rental rate of consumers are low, the manufacturer even needs to produce less if she establishes a new sharing channel.

Optimal retail price and service level in a dual-channel supply chain with reference price effect

<p style='text-indent:20px;'>We study the optimal retail price and service level in a dual-channel supply chain in which the manufacturer may sell products through its online channel and offline retailer. Consumers with channel preference make their purchasing decision based on retail price, service level and channel valuation difference. We consider the reference price effect into a Hotelling utility function to formulate the competition of retail price and service level. We analytically derive the unique equilibrium separately in three power structures: (1) Manufacturer-led Stackelberg game (MS), (2) Retailer-led Stackelberg game (RS) and (3) Nash game (N). Particularly, we characterize the impacts of channel valuation difference and reference price effect intensity on the optimal decision and expected profit. In contrast to the previous literature on the dominance of the supply chain in that the dominance always can raise the dominant enterprise's profit, our findings indicate that supply chain members with channel advantages and channel disadvantages have different preferences for power structure. The member with channel disadvantages should give up dominance. Only when channel valuation difference is significant or reference price effect intensity is weak, the member with channel advantages will fight for dominance. Nash game is highly competitive in that the members only earn less profit. Numerical examples verified theoretical results.</p>

Finding an optimal trade-off retail price promotion strategy using an agent-based simulation

A good pricing strategy is a key factor in the success of a company's products. However, fierce competition and an ever-increasing number of market players are forcing companies to use automated methods and systems to respond in real time to changes in customer purchasing power and competitors' marketing techniques. More importantly, multi-agent modeling tools are used to select the most successful pricing strategy in the first place and consider all factors influencing the final decision. This paper presents a possible variant of a multi-agent model for determining the optimal pricing policy of a company. The results show that the limited rationality and interaction of each agent determines the unique behavior of the system and that the pricing strategy affects the profit and market share of the firm.

Economic implications of equipment sharing under cloud manufacturing

In the development of new information and communication technologies, cloud manufacturing (CMfg) has emerged as a novel and collaborative manufacturing model that enables original equipment manufacturers (OEMs) and clients to share their manufacturing equipment with other clients who do not own equipment. This study focuses on business-to-business (B2B), OEM-to-business (O2B), and B2B&O2B sharing scenarios under CMfg and develops an analytical framework to explore the implications of equipment sharing on retail price, ownership, usage, and environment. Compared with the traditional selling model, the three sharing scenarios result in either higher or lower retail price, ownership, usage, and environmental impact depending on clients' operation cost. Specifically, the higher the operation cost, the lower the retail price. In the B2B scenario, higher ownership, usage, and environmental impact appear only if the operation cost and platform service level are synchronously high/low. Meanwhile, higher ownership and lower usage and environmental impact in B2B&O2B only come with low operation cost. O2B and B2B&O2B surprisingly have the same sharing implications as they involve the same number of equipment units, usage, and environmental impact. Furthermore, this study explores the influence of other crucial factors, such as commission fee, which has opposite effects on ownership in B2B and B2B&O2B, and sharing's effect on the disparity of ownership between heterogeneous clients. • We analyze the economic and environmental long-term implications of Cloud Manufacturing (CMfg) paradigm. • Three scenarios and several distinctive features of equipment sharing in CMfg are considered comprehensively. • Optimal retail price and sharing involvement strategies for the OEM, as well as market-clearing sharing price are proposed.