Research on Pricing Strategy of Online and Offline Supply Chain Based on Channel Preference in the Context of New Retail

In recent years, brick-and-mortar retail has continuously encountered setbacks in the context of the rapid development of the Internet, and many brick-and-mortar stores cannot withstand losses and were closed down. E-commerce also seems to be able to intuitively understand the needs and preferences of consumers. With the continuous competition of online retail, the undifferentiated production of online retail has slowed down the development of e-commerce. *e rise of the new retail model has promoted the production of high-quality products, which has greatly stimulated supply and demand.*e new retail model is able to make better use of existing human and material resources and maximize the use of resources in today’s era of rapid technological changes. Online and offline network competition channels also exert different competitive advantages for different consumers. *is paper studies the competition between physical retail and e-commerce retail and combines centralized decisionmaking and decentralized decision-making for analysis. It also calculates the relative optimal pricing price of e-commerce retail through numerical simulation calculations. Although the best pricing price is obtained after a series of calculations, it is still necessary to comprehensively consider and analyze multiple factors rationally to promote the long-term development of the enterprise. Although supply chain pricing strategies can solve certain problems in market sales to a certain extent, comprehensive analysis and scientifically formulating corporate development strategies are the guarantee of sustainable business operations.


Introduction
e rapid rise of e-commerce has made the situation of the physical retail industry not optimistic, and the undifferentiated production of online retail has caused supply to exceed demand, encourage transformation through national policies, and change the traditional passive pricing strategy of market pull. e new retail model largely circumvents some shortcomings in the traditional e-commerce business process and makes more effective use of the development achievements of the logistics industry. And with the advancement of technology, many products have been updated to meet the higher demands of consumers. On the contrary, consumer purchases have also stimulated the continuous advancement of technology and promoted the development of the economy in a more prosperous direction. e new retail model will become the main mode of operation of the retail market. Hendershott and Zhang [1] studied the pricing strategy of a dual-channel supply chain between a retailer and two manufacturers and analyzed and compared the issue of profit margins and differences in the introduction of online retail channels. Balasubramanian [2] studied the pricing of a number of traditional retailers and manufacturers who introduced online sales channels and found a balanced strategy between them. Kuratan et al. [3] studied the use of price contracts to solve the problems faced in channel competition. Grewal et al. [4] built a framework based on online and offline pricing strategy management to further contribute to the research agenda. Cattani et al. [5] compared a manufacturer that has added online direct sales channels with multiple retailers to study the second-order supply chain equilibrium. Cattani [6] studied that, under the condition of constant wholesale and retail prices, the manufacturer gave the highest price and gave three supply chain pricing methods for reference. Boyaci [7] found through researching inventory competition that, in a dualchannel supply chain composed of a manufacturer and a traditional retailer, a single contract such as quantity discount contract, repurchase contract, and revenue-sharing contract cannot achieve supply chain coordination. Enders and Jelassi [8] constructed a dual-channel supply chain model for manufacturers to open online direct sales channels and discussed the optimal repurchase contracts in the case of information sharing and information nonsharing. Chiang [9] studied the coordination of supply chain by this improved revenue-sharing contract by adding an inventory cost sharing coefficient to the dual-channel supply chain model considering inventory competition. Chen et al. [10] studied the combination of quantity discount contract and two-part pricing contract, which can better realize dualchannel. Coordination of the supply chain will ultimately increase the profits of both manufacturers and traditional retailers. Pietro [11] domestic and foreign scholars' research on dual-channel supply chain mainly focuses on issues such as pricing decisions, service strategies, information sharing, and inventory levels. Park and Keh [12] constructed a dualchannel supply chain model for manufacturers to open direct sales channels. Among them, they separately studied the manufacturer-led and traditional retailer-led pricing models. e above methods have made large or small contributions to the research of dual-channel supply chain.
is article uses existing data and pricing game theory to analyze and research the theme of supply chain through centralized and decentralized decision-making. e documents cited in the article are all priced by retail, but with the development of economy, online economy has become a new sales method. e above literature does not consider the influence of different prices of the same goods online and offline and the influence of different pricing on the pricing of online and offline goods. e second part of the article introduces three kinds of supply structures: online and offline. e third part puts forward the establishment of dual-channel game model and the new retail model; the fourth part evaluates the profit under the supply chain with three channel structures and obtains the influence of related variables on the price in different game models. is paper puts forward that different prices get different decision prices in the game model and finally get vertical comparison in different competitive structures: for the optimal pricing of e-commerce retail, the price under centralized decision is higher than that under decentralized decision, and the promotion effect is the most obvious.

Basic Indicators of the Model
ree types of supply structures were discovered in the consumer groups of manufacturers and retailers: singlechannel supply chain (model 0); manufacturers introduced network channels, called manufacturer dual-channel (denoted as model 0 for model 1); retailers introduced online channels, referred to as Retailer Dual Channels (referred to as model 2), which correspond to the online retail discount rate of physical retail and the degree of consumer recognition of online channels [1,2]. Model 0, model 1, and model 2 proposed in this paper are single-channel supply chain, manufacturer's dualchannel, and retailer's dual-channel, respectively. Model 0 represents single-channel supply, online or offline, model 1 represents online and offline manufacturer's channel, and model 2 represents online and offline retailer's channel. ey deal with different roles and are in important links of the whole supply chain.
When the sales cost of physical channels and online channels are both 0, in a single-channel supply chain (model 0), the net utility of consumers buying products is u 0 � v p ; if u 0 � v p ≥ 0, consumers will buy this channel product. For products, if u 0 � v p < 0, consumers will not buy products; in a dual-channel supply chain (model 1 and model 2), the net utility of consumers buying products on physical channels and online channels is u i1 � v p , u i2 � δv − n p , i � 1, 2 represents the dual-channel of the manufacturer (model 1) and the dual-channel of the retailer (model 2). If u i1 ≥ 0 and u i1 ≥ u i2 , then the consumer net utility is in the interval of 1]. Consumers will purchase products through physical channels; if u i2 > 0 ″ and u i2 > u i1 , the consumer's net utility is in the range of [(η/δ)p, (1 − η/1 − δ)p] , and consumers will buy products on the online channel. At the same time, in order to ensure the existence of both physical and online channels, the demands of both channels must be positive, so there are the following assumptions. Assume 60 < η < δ < 1.
In order to ensure the existence of dual channels, when the consumer's valuation is 1, it is set that consumers must purchase the product through physical channels; when the consumer's valuation is (η/δ)p, it is assumed that consumers must purchase the product through online channels. In other words, for consumers, v � 1, u i1 ≥ 0 and u i1 ≥ u i2 , V � η/δ, u i2 ≥ 0 and u i2 ≥ u i1 ; therefore, 0 < η < δ < 1 can be obtained.

The Establishment of a Dual-Channel Game
Model and the Establishment of a New Retail Model

Model 0.
With manufacturer's wholesale price w and retailer's retail price p, through reverse induction, the retailer's decision-making problem is given as e inverse function of the retailer from the first-order optimal condition is Get the manufacturer: According to the first-order optimal advantage conditions, the manufacturer's optimal wholesale price w * 0 � 1/2 .

Model 1.
From the previously obtained p, and p, the manufacturer, as the leader of the Stackelberg game model, sets the wholesale price w, so the retailer's decision-making problem is According to the characteristics of the required function, the retailer's response function is optimally erefore, the manufacturer's decision-making problem is e manufacturer's decision-making problem is about giving the second concave of the wholesale price and obtaining the optimal wholesale price according to the existing conditions: en the reaction function is introduced to obtain the optimal retail price of the retailer's physical channel as Bringing w * 1 , p * 1 into can get the optimal demand of model 2.

Model 2.
With the decision-making problem obtained from the previous According to the first-order optimal condition of the concave shape of the given function, the response function of the retailer is obtained: According to the retailer's reaction function, the manufacturer's decision-making problem is e manufacturer's decision-making problem is about the second concave, and the optimal wholesale price can be obtained according to the first-order optimal condition: By bringing into the reaction function, the optimal retail price of the retailer's physical channel can be obtained: Appropriately bring w * 2 , p * 2 into the expression that can obtain the optimal demand of model 2, the most profitable, etc.
e common feasible conditions of Model 1 and Model 2 are In the region R, the profit of each channel of the models 1 and 2 is all positive [5].

Analysis of Online and Offline Models in the Context of New Retail.
(1) e influence of service level on the pricing of retail enterprises (S r, S R ).

Corollary 1.
e optimal price of P * r physical retail is positively correlated with its price level S r , so when decentralizing decision-making [6], the entity-led Stackelberg game: Stackelberg game dominated by e-commerce: Nondominant Bertrand model: Game without dominance under centralized decisionmaking: ere is a positive correlation between P * r , the optimal retail price of e-commerce, and S r , the retail price level of e-commerce [7].
When decentralizing decision-making, the entity-led Stackelberg game: Stackelberg game dominated by e-commerce: Nondominant Bertrand model: Game without leading when centralizing decisionmaking: Corollary 3. e optimal retail price of e-commerce is P * R positively correlated with the service level of logistics enterprises S TR [8].
When decentralizing decision-making, the entity-led Stackelberg game: Stackelberg game dominated by e-commerce: Nondominant Bertrand model: Game without leading when centralizing decisionmaking: Because

Corollary 4.
Under the decentralized decision-making, the physical retail optimal price is P * r positively correlated with the logistics enterprise price P * TR . Under centralized decision-making, there is no correlation between P * TR , the physical retail optimal price, and the logistics enterprise price, P TR . e optimal retail price of e-commerce is P * R negatively correlated with the service level of logistics enterprises S TR .
When decentralizing decision-making, the entity-led Stackelberg game: Stackelberg game dominated by e-commerce:

Complexity
It is easy to get (zf/zδ)| (η,0) � η 4 − 10η 3 < 0, | (η,η) � 4η 2 (η − 1) 2 > 0, is shows that whether manufacturers or retailers introduce online channels, their profits will increase for manufacturers. erefore, as the leader of the game, manufacturers will introduce online channels. e indispensable advantage of retail channels in the market depends on what kind of preferential decision is used to stretch the profit front. But from the perspective of occupying the market, the introduction of online channels by retailers happens to be the most beneficial. In the area B shown by the retailer, the more preferable item is to introduce the network channel by itself, and in the area A, the manufacturer is still inclined to open the network channel. Going forward, whether manufacturers or retailers introduce online channels, retailers' marginal profits and demand for physical channels are reduced, so the profits of physical channels will decrease, especially after the introduction of online channels, through further observation. e loss suffered by physical channels is incomparable to the profits made by retailers introducing online channels; that is, the overall profit of the supply chain will be reduced; however, the profits brought by manufacturers introducing online channels are higher than the losses of physical channels, namely, supply. e overall profit of the chain will increase [10]. From this, it can be obtained that if you choose to introduce online channels under channel preference, you will get better profits when you choose online channels.

Evaluation of the Impact of Related Variables in Different
Models on Pricing. Using centralized decision-making and decentralized decision-making to analyze the different competition structures established, in the existing research on the online and offline dual-channel supply chain, the object of the study is not only the e-commerce itself, but also the service level of logistics enterprises. E-commerce service level, logistics service, and pricing affect the changes in the optimal pricing of two different retail entities, as shown in Table 1.
Studies have shown that comparing the service levels of logistics companies under all competition structures will have a positive and relevant impact on e-commerce retail prices. However, when logistics companies' service levels are also positively correlated with physical retail prices, logistics companies' service levels have a positive impact on e-commerce retail prices. e impact will be greater than the impact of physical retail prices [11].

Numerical Simulation Analysis.
rough the above rational analysis, according to the relevant literature and related numerical simulations, the influence of the service levels of the two retail companies and the service and price levels of the logistics companies on the optimal prices of physical and e-commerce retail under decentralized decision-making and centralized decision-making is analyzed according to relevant literature and related numerical simulations. e basic parameters of the optimal pricing model in the new retail dual-channel supply chain are shown in Table 2.
e corresponding parameter values in Table 2 are calculated according to the sales and optimization formulas and are theoretical values obtained from the influence and correlation of different parameters on different prices.
Analyze the impact of physical retail service levels on retail prices, and through the formula model in the previous section and the above numerical parameters, the impact of physical retail services and levels on the optimal price of physical retail and e-commerce retail can be obtained, respectively, as shown in Table 3. e best price of e-commerce sales can be obtained through the price level of e-commerce information.
e formula is a model obtained by guiding the optimal price impact of physical retail and e-commerce retail through physical retail service and level.
Run the above 7 formulas in Matlab software to get Figure 1. When decentralizing decision-making: (i) Y1 is the best decision-making price of the entityled pricing in the Stackelberg game. (ii) Y2 is the best decision price for physical retail pricing led by e-commerce in the Stackelberg game. (iii) Y3 is the best decision-making price for physical retail pricing without dominant in the Bertrand game. (iv) Y4 is the best decision price of e-commerce retail pricing dominated by entities in Stackelberg game. (v) Y5 is the best decision price of e-commerce retail pricing dominated by e-commerce in Stackelberg game. (vi) Y6 is the best decision price of e-commerce retail pricing without dominance in Bertrand game. (vii) Y7 is the optimal price of e-commerce retail in the nondominant game.
(1) Macroscopic Analysis. In terms of model quantity: e optimal price of e-commerce retail under centralized decision-making is not affected by the physical retail service level. Overall trend: with the improvement of physical retail service level, the optimal pricing of the two retailers, the four game models of the entity-led Stackelberg game under decentralized decision-making, e-commerce-led Stackelberg game, nondominant Bertrand game, and game under centralized decision-making are all improving.
(2) Microanalysis. Retailer horizontal comparison: e physical retail service level has a more obvious promotion effect on the optimal price of the channel than the optimal price of the nonlocal channel. Make Indicates the total market size of retail enterprise products 600 S r S R S TR e service level of physical retail, e-commerce retail, and logistics companies 9, 9, 9 α 1 e elasticity coefficient of market demand to price 5 α 2

Complexity
Cross elasticity coefficient of market demand to price 3 β 1 e elasticity coefficient of market demand to service 5 β 2 Cross elasticity coefficient of market demand to service 1 λ Consumers' channel preference coefficient for physical retail 0.3 η Service cost factor 0.8 θ Cost optimization factor under big data technology 0.8 ↑ means positive correlation, ↓ means negative correlation, O means unable to judge, and "-"means no effect. In Table 1, P r represents the retail price of ecommerce and P R represents the physical retail price. P r − P R represents the difference between physical and online prices. S r represents the retail price level of e-commerce, S TR represents the service level of logistics enterprises, and P TR represents the price of logistics enterprises. Add " * " to indicate the optimal value. Complexity a vertical comparison of its different subjects in the competition structure: the centralized decisionmaking is superior to other several pricing models, and the promotion effect is the most obvious.
When centralizing decision-making: e optimal decision price of physical retail pricing is in the y4 game. e figure shows the following: e impact of e-commerce retail service levels on retail prices: through the model formulas in the previous chapter and the parameter assumptions in the above table, the effect of e-commerce retail service levels on the optimal price of physical retail and e-commerce retail can be solved, respectively, as shown in Table 4.
Run the above 7 formulas in the Matlab software to get Figure 2, where we have the following.
When decentralizing decision-making: Y1 is the best decision price of the entity-led retail pricing in the Stackelberg game. Y2 is the best decision-making price for physical retail pricing led by e-commerce in the Stackelberg game. Y3 is the best decision-making price for physical retail pricing without leading in the Bertrand game. Y4 is the best decision-making price of e-commerce retail pricing led by entities in the Stackelberg game. Y5 is the best decision price of e-commerce retail pricing in the Stackelberg game. Y6 is the best decision-making price for e-commerce retail pricing without leading in the Bertrand game. When centralizing decision-making: Y7 is the e-commerce retail optimal price in the nondominant game. e following can be seen from the figure: (1) Macroscopic analysis: a. e quantity of models: the optimal price of physical retail under centralized decision-making is not affected by the e-commerce retail service level. b. e overall trend: as the e-commerce retail service level increases, the e-commerce retail price, optimal pricing, is improved in four game models: the entity-led Stackelberg game under decentralized decision-making, the Stackelberg game led by e-commerce, the nondominant Bertrand game, and the game under centralized decision-making. (2) Microanalysis: a. Horizontal comparison of retailers: e optimal retail price of e-commerce and the service level of e-commerce are positively correlated, and the optimal price of physical retail and the e-commerce service level are first negatively correlated and then positively correlated. At the same time, the e-commerce retail service level has a more obvious influence on the optimal price of this channel than the optimal price of the nonlocal channel. b. Vertical comparison of different competition structures: For the optimal pricing of e-commerce retail, the price under centralized decision-making is higher than the three game models under decentralized decision-making, and the promotion effect is the most obvious.

Conclusion
It can be seen that, in the context of new retail, the channel preference is mainly reflected in the introduction of network channels, which has a positive effect on the overall development of the supply chain and will increase the overall profit of the supply chain. e problem of supply chain pricing is unavoidable at any time. Even if the times are advancing and technology will continue to evolve, the relationship between the various factors in them is always interacting and influencing each other. Concentrating on solving the problems within the supply chain is the crux of the problem. Both online and offline channels should pay attention to their own service level. e improvement of service level will increase the profit to a certain extent. erefore, for enterprises, it is necessary to not only improve  8 Complexity the service level, but to pay attention to the integration of multiple factors [12]. Analyze and promote the long-term development of the enterprise. For choosing a logistics company, it should comprehensively evaluate its service level and price, so as to promote the increase of its own interests, meet the ever-evolving market demand, and increase the overall profit. e continuous progress of emerging technologies promotes the new retail business to a higher level. e development and application of big data technology by major groups and the rapid progress of Internet and Internet of ings technologies all promote the various entities in the new retail industry. e major groups and companies have joined forces and cooperated with each other, promoting the one-stop linkage service from product manufacturing to storage and maximizing the use of resources. Only in this way will it bring greater development space and more benefits to the enterprise.

Data Availability
e experimental data used to support the findings of this study are available from the corresponding author upon request.