Pricing and coordination models before and after the integration of omni-channel supply chain by mobile internet

Abstract

Under the omni-channel supply chain by mobile internet, considering both cooperation and competition, this article establishes the pricing model before and after the integration of the omni-channel supply chain by mobile internet and the coordination strategy model under the mobile internet e-commerce logistics cooperation, so as to obtain the wholesale price decision and retail price decision and compensation decisions etc. of supplier S. Furthermore, it can also obtain the corresponding price of retailer T accordingly. Based on the analysis of the above two models, numerical simulations are carried out to compare the optimal decision-making volume before and after the integration of the omni-channel supply chain by mobile internet and the overall profit level. With the help of the numerical simulation results of the above models, the effectiveness of the integration of the omni-channel supply chain by mobile internet is demonstrated which achieving win-win and multi-win in both greater breadth and depth in the supply chain.

Keywords

Mobile internet pricing model omni-channel supply chain

1. Introduction

According to the “National Consumer Goods Retail Report 2020” released by the National Bureau of Statistics, the total retail sales of consumer goods in 2020 was 3.92 trillion yuan, of which the total mobile internet retail sales in 2020 was 11760.13 billion yuan, and the mobile internet retail sales of physical goods was 97590.3100 million yuan, increasing 10.9% and 14.8% over the previous year. The total mobile internet retail sales in 2020 accounted for 30% of the total retail sales of consumer goods [1].

With the rapid development of mobile Internet and e-commerce, enterprises can use the supply chain management system to coordinate and run their business online. Both parties in the supply chain can cooperate in real-time management and realize information sharing, so as to master the entire procurement and supply process, find problems and make timely feedback and improvement, and to realize the transformation from extensive management to refined management.

It can be seen from the above data that the network economy more and more becoming an important part of the economy in China. This has caused a great impact on the real economy, especially on entity stores, so China’s entity stores urgently need to be transformed and upgraded [2, 3]. Companies that previously only need to manage entity channels are looking at the trend to introduce mobile internet sales to resist the impact of mobile internet shopping on entity sales, hoping to maintain or expand the market through mobile internet channel sales [4, 5, 6]. On the other hand, some e-commerce companies have adopted bold innovations, linking mobile internet channels, entity channels, and logistics to form a brand-new retail model of “omni-channel” [7]. The whole e-commerce industry recognizes and promotes this concept, exploring the horizontal integration of multiple channels such as mobile internet and entity has become the focus of many companies [8, 9, 10].

2. Describe the assumptions and build the model

Thinking about such a problem: First consider a simple traditional retail model, assuming that the supply chain contains only one supplier S and one traditional retailer T. Suppliers can either choose to sell products directly to consumers mobile internet, or they can choose to sell to consumers through traditional retail wholesale and retail models, that is, use traditional entity store sales channels to sell to consumers [11, 12, 13]. Again, suppose that the consumer’s initial willingness to buy fresh products is demand (D), Cost G, to the physical store [14]. Consumers can also choose to buy goods entity directly in physical stores, but they must be aware that consumers’ willingness to buy when buying products mobile internet will decrease with the extension of the delivery time [15]. Suppose the consumer’s demand is $e^{-at}d$ . As shown in Table 1, when $({{a}>0})$ , $a_{1}$ and $a_{2}$ , represent the consuming willingness before and after joining the e-commerce logistics cooperation. At the same time, $({a_{1}>a_{2}})$ for this article assumes that the services provided by traditional mobile internet retailers are more popular with consumers [16]. Finally, according to the needs of the problem description, suppose that the retail price of supplier S is P ${}_{\text{S}}$ while the retail price of the traditional retailer is P ${}_{\text{t}}$ .

Table 1
Symbol description in the model

Symbol	Definition	Symbol	Definition
p ${}_{\text{t}}$	Selling price of retailer T	W	Wholesale price of supplier
p ${}_{\text{s}}$	Direct selling price of supplier S	C	Fixed cost for cargo delivery
G	Logistics cost for entity store T	h ${}_{\text{s}}$	Mobile internet distribution cost coefficient
a ${}_{1}$	Product purchase intention index before	h ${}_{\text{t}}$	Entity distribution cost coefficient
	e-commerce logistics cooperation
d	Consumer’s initial demand	$\lambda$	Unit compensation coefficient
k	Ratio of mobile internet and entity distribution	t	Stipulated delivery time
	cost coefficient
r	Retailer’s share of revenue sharing	a ${}_{2}$	Product purchase intention index after e-commerce
			logistics cooperation

Hypothesis 1: Supplier S is in a controlling position in the market. First, set a wholesale price W and a retail price P ${}_{\text{s}}$ , hen traditional retailer T sets a retail price P ${}_{\text{t}}$ , with reference to the wholesale price W set by the supplier. Supplier S does not have its own logistics services can only be delivered through third-party logistics services. In this circumstance, delivery cost including both fixed cost C and variable cost $\frac{1}{2}h_{s}({1-t})^{2}$ which is related to delivery time t. Suppose t $\in$ (0,1), when t $\to$ 0,

$\displaystyle e^{-at}d\to{d},c+\frac{1}{2}h_{s}({1-t})^{2}\to c+\frac{1}{2}h_{% s},\text{ while},t-1,e^{-at}d\to e^{-at}{d},c+\frac{1}{2}h_{s}({1-t})^{2}\to{c}$

Hypothesis 2: On the basis of Hypothesis 1, supplier S and retailer T carry out e-commerce logistics cooperation and clarify the assignment of tasks between the two parties in the cooperation [17]. Entity traditional retail entity stores can choose to be responsible for product distribution and logistics, or they can choose third-party logistics delivery, and complete the delivery task within the promised certain time [18]. Assuming the entity traditional physical retail distribution cost coefficient $h_{{t}}$ , the e-commerce logistics cooperation between supplier S and retailer T makes the traditional retail entity store become the “front warehouse” of the supply chain distribution channel, which can save costs, so assume $h_{s}>h_{t}$ . But it should be noted that when retailer T replaces supplier S to provide logistics services, the supplier will pay a certain amount of compensation to the retailer. On this basis, the supplier S and the retailer S determine the wholesale price, and then according to the wholesale price, respectively determine the supplier’s direct selling price and the retail price of the entity traditional entity store.

Hypothesis 3: Based on the assumption that the second mobile internet and entity supplier S and the retailer T will carry out e-commerce logistics cooperation, the price will be further adjusted, and the participants in all links of the omni-channel supply chain will jointly sign a revenue sharing contract [19, 20]. Consumers generally prefer a more intuitive shopping experience such as the services provided by entity traditional physical stores, so they transfer the right to set prices to entity traditional retailers, and then distribute the benefits according to the above-mentioned pricing method.

In the three hypothetical situations, after both the supplier S and the retailer T set prices, consumers make shopping strategies based on the prices. Assume that consumers are risk-neutral and satisfy their own needs to the maximum [21]. Therefore, consumers have two different shopping tendencies: One is to purchase from the mobile internet channel of supplier S [22], and expect surplus is $U_{s}=e^{-\beta t}d-p_{s}$ . The other is to purchase from the entity channel of the traditional retailer T [23], and expect surplus is $U_{t}=d-P_{t}-s$ .

3. Coordination strategy model before channel integration

According to hypothesis 1, supplier S and retailer T do not have mobile internet and entity logistics cooperation, neither do they entrust third-party logistics distribution, and supplier S conducts logistics distribution services on its own. The game between supplier S and retailer T is as follows:

Supplier S first sets the wholesale price W;

Supplier S and retailer T respectively determine the direct selling price Ps and retail price Pt in the mobile internet and entity channels;

Realize supplier S and retailer T Profit.

Calculate the profit function of supplier S:

$\displaystyle\text{II}_{s}={W}{D}_{t}+{p}_{s}{D}_{s}-\left({{c}+\frac{1}{2}{h}% _{s}({1-{t}})^{2}}\right){D}_{s}$ (1)

Calculate the profit function of retailer T:

$\displaystyle\text{II}_{t}=({{p}_{t}-{w}}){D}_{t}$ (2)

According to the assumption that the profit of a supplier S comes from two parts: the first part of the profit comes from the supplier S’s wholesale supply channels, and the supplier S supplies products to the retailer T at the wholesale price W; the second part of the profit comes from the direct sales of the supplier S Channel, that is, the supplier S directly sells products to consumers in the direct sales channel. Retailer T’s profits only come from the wholesale supply channels provided by supplier S, and retailer T sells products to consumers at retail prices. Assume $a=e^{-at}d$ , before channel integration, the optimal decision of supplier S and traditional retailer T is as follows:

$\displaystyle\left\{\begin{array}[]{l}p_{t1}=-\frac{-ah_{s}t^{2}+2ah_{s}t-4h_{% s}t^{2}+2a^{2}-2ac-ah_{s}+4as+8h_{s}t+4a-8c-4h_{s}+24s-24}{4(a+8)}\\ p_{t1}=\frac{3ah_{s}t^{2}-6ah_{s}t+8h_{s}t^{2}-2a^{2}+6ac+3ah_{s}+4as-16h_{s}t% +20a+16c+8h_{s}}{4(a+8)}\\ w_{1}=\frac{-ah_{s}t^{2}+2ah_{s}t+2a^{2}-2ac-ah_{s}-16s-16}{4(a+8)}\end{array}\right.$ (3)

Then, according to the above assumptions, the optimal profits of supplier S and traditional retailer T are as follows:

$\displaystyle\text{II}_{s1}=w_{1}D_{t1}+p_{s1}D_{s1}-\left({c+\frac{1}{2}h_{s}% ({1-t})^{2}}\right)D_{s1}$ (4) $\displaystyle\text{II}_{t1}=({p_{t1}-w_{1}})D_{t1}$ (5)

According to hypothesis 1, conclusion 1: when supplier S and traditional retailers do not have mobile internet and entity logistics cooperation, that is, when there is no integrated channel, according to the above Eqs (4) and (5), the optimal wholesale price determined by the supplier S is negatively correlated to logistics distribution cost coefficient ${h}_{s}$ , while the result of traditional retailer T is opposite to that of supplier S. The optimal direct selling price and optimal retail price of retailer T are positively correlated with distribution cost coefficient ${h}_{s}$ .

It can be seen from conclusion 1 that when the distribution cost coefficient ${h}_{s}$ is getting higher, the distribution cost is also getting higher, supplier S can indeed obtain a small portion of profits through direct sales channels. However, supplier S is more inclined to take consumers from mobile internet sales shift to entity sales, because this can bring more profits. Therefore, supplier S will slightly lower the wholesale price $W_{1}$ and increase the direct sales price $P_{{S1}}$ to reduce direct mobile internet sales, so that it can obtain more orders from traditional entity store retailers through retailer T’s wholesale supply channels and obtain more profits. According to the above Eqs (4) and (5), as the distribution cost coefficient ${h}_{{s}1}$ increases, although the wholesale price W1 is decreasing, the retailer T will increase the retail price ${P}_{{s}1}$ , so the retailer will obtain higher profits. The reason lies in the price advantage. On the one hand, supplier S actively adjusts prices to promote consumers to move to entity traditional retail entity stores; On the other hand, a large number of consumers voluntarily flock to entity traditional retail entity stores. Therefore, the traditional retailer T will gradually gain a monopolistic market position in the market, so that it can use the monopolistic market position to increase retail prices and obtain higher profits.

4. Coordination strategy model under e-commerce logistics cooperation

According to hypothesis 2, supplier S and traditional retailer T carry out mobile internet and entity logistics cooperation. Retailer T is responsible for logistics and distribution. Therefore, it will be partially compensated by supplier S, and then retailer S will help supplier S complete the distribution of products Serve. The game between supplier S and retailer T is as follows:

Supplier S signs an e-commerce logistics cooperation agreement with traditional retailer T. Traditional retailer T first determines the unit compensation coefficient of the e-commerce logistics cooperation, and then supplier S sets the wholesale price W;

Supplier T and traditional retailer S determine the direct selling price PS and retail price Pt respectively according to the wholesale price W;

Supplier S and traditional retailer T realize their respective profits.

Calculate the profit function of supplier S as:

$\displaystyle\text{II}_{s}=wD_{t}+p_{s}D_{s}-\lambda D_{s}$ (6)

Calculate the profit function of traditional retailer T as:

$\displaystyle\text{II}_{t}=({p_{t}-w})D_{t}-\left({c+\frac{1}{2}h_{t}({1-t})^{% 2}}\right)D_{s}+\lambda D_{s}$ (7)

According to hypothesis 2, the sources of profit for supplier S come from two parts. The first part of profit comes from supplier S’s wholesale supply channels, and supplier S supplies products to retailer T at wholesale price W; the second part of profit comes from the direct sales channel of supplier S, that is, the supplier S directly sells products to consumers in the direct sales channel. In hypothesis 2 and hypothesis 1, the profits of traditional retailer T also come from two parts: the first part is the profit derived from the sales of products from supplier S to consumers; the second part is derived from the supplier S is the compensation given in the logistics cooperative distribution service. Similarly, let $b=e^{-\beta t}d$ . According to hypothesis 2, supplier S and traditional retailer T carry out mobile internet and entity logistics cooperation, and the optimal decision volume of supplier S and traditional retailer T is calculated as follows:

$\displaystyle\left\{\begin{array}[]{l}p_{t2}=-\frac{6(s-1)}{(b+8)}\\ p_{s2}=\frac{bh_{t}t^{2}-2bh_{t}t+2h_{t}t^{2}+2bc+bh_{t}-4h_{t}t+12b+4c+2h_{t}% }{2(b+8)}\\ w_{2}=\frac{h_{t}t^{2}-bs-2ht-b+2c+h-4s+4}{(b+8)}\\ \lambda_{2}=\frac{2h_{t}t+b^{2}+2bs-4h_{t}t+2b+4c+2h_{t}}{(b+8)}\end{array}\right.$ (8)

According to hypothesis 2, conclusion 2 can be drawn: when supplier S and traditional retailer T carry out mobile internet and entity logistics cooperation, according to Eq. (8), supplier S’s best direct selling price and best wholesale price are both positively correlate to the distribution cost coefficient $h_{t}$ in e-commerce logistics cooperation. However, the traditional retailer T is not sensitive to the distribution cost coefficient $h_{t}$ , because the traditional retailer T will receive the distribution compensation for e-commerce logistics cooperation from the supplier S, thus the distribution cost coefficient $h_{t}$ will not affect the traditional retailer T has an impact. As in Hypothesis 1, the optimal direct sales price and optimal retail price of retailer t are positively correlated with the distribution cost coefficient $h_{t}$ .

It can be seen from conclusion 2 that when the distribution cost coefficient $h_{t}$ is high, supplier S will still choose to maintain the sales volume of direct sales channels, because when signing an e-commerce logistics cooperation agreement with traditional retailer T, traditional retailer T needs to bear a heavier logistics. Therefore, supplier S will slightly increase the wholesale price and give retailer S more profit. At the same time, the increase in wholesale price will lead to an increase in the price set by retailer T, which will also inhibit consumer demand in traditional retail entity stores. At the same time, in this way, increasing the wholesale price can promote more consumers to purchase products through direct sales channels, so the supplier S will instead get more profits. For traditional retailer T, on the basis of carrying out e-commerce logistics cooperation, the higher distribution cost will also be compensated by the higher supplier S. Then, in the end, when the price of product wholesale supply channels rises, the profit of traditional retailer T will decrease, and traditional retailer T will compensate for its own logistics costs through higher logistics distribution compensation coefficients, and ultimately to earn more profits for itself.

5. Coordination strategy model under e-commerce logistics cooperation and price integration

According to hypothesis 3, on the basis of mobile internet and entity logistics cooperation between supplier S and retailer T, supplier S integrates sales prices to complete the integrated operation of mobile internet and entity sales, and supplier S and retailer T share profits together. However, under such circumstances, the traditional entity retailer T will choose the third-party logistics service, and provide certain compensation to the third-party logistics according to the conditions in the second hypothesis. The game between supplier S and retailer T is as follows:

Supplier S signs an e-commerce logistics cooperation agreement with traditional retailer T. Traditional retailer T first determines the market unit profit, and then supplier S determines the profit-sharing ratio between the two parties; Traditional retailer T uniformly sets mobile internet and entity sales prices; Supplier S and traditional retailer T realize their respective profits.

The mobile internet and entity profit functions are as follows:

$\displaystyle\left\{{{\begin{array}[]{l}{\text{II}_{t}=r({p({D_{s}+D_{t}})})-% \left({c+\frac{1}{2}h_{t}({1-t})^{2}D_{s}}\right)+\lambda D_{s}}\\ {\text{II}_{s}=({1-r})({p({D_{t}+D_{S}})})-\lambda D_{s}}\\ \end{array}}}\right.$ (9)

Derivation of the profit function of the traditional retailer T can be obtained, and the optimal decision quantity of the price is:

$\displaystyle p_{3}=\frac{h_{t}t^{2}+2br-2h_{r}t+2c+h_{t}-2\lambda}{4r}$ (10)

Substitute Eq. (10) into Eq. (9), and then perform simultaneous derivation. It can be seen that on the basis of mobile internet and entity logistics cooperation between supplier S and retailer T, when carrying out price integration, the optimal decision volume of supplier S and traditional retailer T is calculated as:

$\displaystyle\left\{\begin{array}[]{l}\lambda_{3}=-\frac{1}{4s(b+s-1)(b-1)}(b^% {3}h_{t}t^{2}+2b^{2}h_{t}st^{2}+2bh_{t}s^{2}t^{2}-2b^{3}h_{t}t-4b^{2}h_{t}st-3% b^{2}h_{t}t^{2}\\ {}-4bh_{t}s^{2}t-4bh_{t}st^{2}-2h_{t}s^{2}t^{2}+2b^{4}+2b^{3}c+b^{3}h_{t}+12b^% {2}s+4b^{2}cs+2b^{2}h_{t}s\\ {}+6b^{2}h_{t}t+24b^{2}s^{2}+4bcs^{2}+2bh_{t^{2}}s^{2}+8bh_{t}st+3bh_{t2}t^{2}% +16bs^{3}+4h_{t}s^{2}t+2h_{t}st^{2}\\ {}-6b^{3}-6b^{3}c-3b^{2}h_{t}-24b^{2}s-8bcs-4bh_{t}s-6bh_{t}t-24bs^{2}-4cs^{2}% -2h_{t}s^{2}\\ {}-4h_{t}st-h_{t}t^{2}+6b^{2}+6bc+3bh_{t}+12bs+4cs+2h_{t}s+2h_{t}t-2b-2c-h_{t}% )\\ r_{3}=-\frac{1}{4sb(b+s-1)}(b^{2}h_{t}t^{2}+2bh_{t}st^{2}-2b^{2}h_{t}t-4bh_{t}% st-2bh_{s}t^{2}-2h_{t}st^{2}+2b^{3}+2b^{2}c\\ {}+b^{2}h_{t}+8b^{2}s+4bcs+2bh_{t}s+4bh_{t}t+8bs^{2}+4h_{t}st+h_{t}t^{2}-4b^{2% }-4bc-2bh_{t}-8bs\\ {}-4cs-2h_{t}s-2h_{t}+2b+2c+h_{t}\\ p_{3}=\frac{bs}{(1-b)}\end{array}\right.$ (11)

It can be known from hypothesis 3 that on the basis of mobile internet and entity logistics cooperation between supplier S and retailer T, after supplier S integrates the sales price, when the distribution cost coefficient $h_{t}$ under the e-commerce logistics cooperation is relatively large, traditional retailer T will obtain the compensation from the e-commerce logistics cooperation with supplier S, so $h_{t}$ will not affect the optimal retail price of traditional retailers. However, when there is logistics compensation, the cost of sales of the traditional retailer T and the optimal coefficient of the cost of sales will not show a positive correlation [24]. Therefore, the sales price and the cost of sales of the traditional retailer T will also not have a positive correlation, which will lead to the increase of the product optimal distribution coefficient of retailer T and supplier S must therefore give a higher compensation coefficient for e-commerce logistics cooperation. When signing a mobile internet and entity logistics cooperation agreement, supplier S will definitely limit the profit distribution traditional of retailer T, so the profit-sharing coefficient and the compensation coefficient of e-commerce logistics cooperation are negatively related when signing the sharing contract [25]. On the basis of mobile internet and entity logistics cooperation between supplier S and retailer T, the integrated sales price of supplier S will also reduce unnecessary logistics and transportation, and therefore reduce unnecessary logistics and distribution costs [26].

Conclusion 3 can be drawn from the hypothesis 3: based on the mobile internet and entity logistics cooperation between supplier S and retailer T, the demand for mobile internet wholesale supply channels is $D_{s}=0$ . It can be seen from Eq. (11) that after mobile internet and entity omni-channel e-commerce logistics cooperation, through e-commerce logistics cooperation and price integration, supplier S and traditional retailer T will share the distribution of profits through channels, reducing the cost of third-party logistics services and increasing the efficiency of the entire omni-channel supply chain.

6. Comparative analysis of optimal benefits of omni-channel supply chain integration

The above discusses the coordination strategy content of the three channel integration models, and the total profit function after the three-channel integration is calculated as:

$\displaystyle\text{II}=p_{t}D_{t}+p_{s}D_{s}-\frac{1}{2}h({1-t})^{2}D_{s}$ (12)

Assume the values of the parameters: $s=$ 0.1, $c=$ 0.1, $h_{s}=$ 1, $a_{1}=$ 0.6, $a_{2}=$ 0.3, then assume the value range of the delivery time according to the hypothesis 2, and assume the value range of the delivery cost coefficient ratio k according to the problem description. Therefore, the optimal income of channel integration under the three models is calculated.

The mobile internet and entity logistics cooperation between supplier S and retailer T can greatly reduce the wholesale price of supplier S, but it will increase the direct selling price of supplier S and the retail price set by traditional retailer T. According to the calculation results of the above three models, after signing a mobile internet and entity logistics cooperation agreement with supplier S, traditional retailer T undertakes the logistics and distribution services provided by supplier S, so it has to pay more for the corresponding logistics and distribution costs. At the same time, after setting the wholesale supply price, supplier S can significantly reduce the wholesale supply price in hypothesis 2, and entity traditional retailer T has also been compensated for the cost of logistics and distribution services. Retailer T will be willing to increase the price in hypothesis 2. Thereby, the increasing retail price promotes more consumers to choose mobile internet purchasing channels. At the same time, supplier S will use the signed mobile internet and entity logistics cooperation agreement and price adjustment strategy to increase the direct selling price and thus obtain higher profits.

In hypothesis 2, the traditional retailer T is in a dominant position of monopoly to formulate compensation for logistics and distribution costs by its strong position. In order to prevent the reduction in profits, supplier S will increase the direct selling price for more profits to compensate for the retailer’s logistics matching service, and suppose the overall purchase scale of the consumer group is: $D=1-\frac{p_{s}}{e^{-\beta_{2}t}}$ , which will decrease with the increase in direct selling prices. Therefore, it will reduce the overall total profit for the traditional retailers T to promote consumers to choose mobile internet supplier S to cooperate in mobile internet and entity logistics and distribution by increasing the selling price of entity retail stores.

In the hypothesis 3, the result of calculating the optimal decision quantity shows that the supplier S and the traditional retailer T jointly set the selling price of the product, and promote consumers to choose entity store purchase channels, which will reduce the overall logistics and distribution service cost of the supply chain. In this case, the retail price of products in the mall will decrease with the extension of the delivery time, thereby reducing the scale of consumer demand, and the total profit of the entire supply chain system will also decrease.

7. Conclusion

Supplier S and retailer T are developing mobile internet and entity logistics cooperation, however, which is not beneficial to all the suppliers S. It is more suitable for slow-developing supplier companies that do not have much financial support to realize new retail based on mobile internet sale. The model promotes consumers to choose more mobile internet purchase needs, thereby expanding the market size and obtaining more profits. For enterprises with capital strength, considering the issue of delivery timeliness, traditional retailers will be more willing to carry out mobile internet and entity logistics cooperative delivery services, and then make price adjustments. On the contrary, suppliers are more reluctant to cooperate in logistics distribution and will have a stronger willingness to cooperate in price adjustments.

On the basis of mobile internet and entity logistics cooperation between supplier S and retailer T, the mobile internet and entity omni-channel supply chain conducts integrated operations. In order to reduce the cost of logistics and distribution services, traditional retailers may choose to promote more consumers making entity consumption, that is, guiding consumers to make entity purchases through price. Because at this time, for merchants and retailers, the level of profit is related to the market position, and more depends on the bargaining power of the two parties on the market advantage. For all participants in the entire omni-channel supply chain, when carrying out mobile internet and entity logistics cooperation and price integration, on the one hand, it can improve the resource utilization rate of each link in the omni-channel supply chain, and make products sold to consumers at more reasonable prices. On the other hand, it can also promote the total product demand on the market and maximize the total profit of the entire omni-channel supply chain.

This article summarizes the content of omni-channel supply chain integration, analyzes the process of data information transfer between subjects in each link of the supply chain, analyzes and studies the specific path of omni-channel supply chain integration, and then transitions to analyzing the pricing model before and after the omni-channel supply chain integration. After further study on three different levels of channel integration, this article analyzes the different pricing options of suppliers and retailers under different integration situations, and compares the optimization benefits of the three channel integrations. By analyzing the omni-channel supply chain integration content and coordination model, it is more conducive to further analyzes on the optimization problem of the omni-channel supply chain.

It can be seen that e-commerce under the mobile Internet is a new business model aimed at creatively promoting the development of the industry. Through the mobile Internet, supply chain companies can be actively found by a wider range of cargo owners and customers, and can expand business nationwide and even worldwide. Trading companies and factories can more quickly find the most cost-effective logistics company while online logistics is committed to attracting the world’s largest number of cargo owners with logistics needs and logistics companies that provide logistics services to provide a more neutrality, honest and free online logistics trading market. Within such an online trading market, both logistics supply and demand sides will be able to reach transactions more efficiently.

Footnotes

Acknowledgments

This article was supported by National Natural Science Foundation of China (No. 71774109).

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Pricing and coordination models before and after the integration of omni-channel supply chain by mobile internet

Abstract

Keywords

1. Introduction

2. Describe the assumptions and build the model

Table 1 Symbol description in the model

Footnotes

Acknowledgments

References

Table 1
Symbol description in the model