Research on Advertising and Pricing in E-Supply Chain Under Different Dominant Modes

Yuyan WANG; Zhaoqing YU

doi:10.21078/JSSI-2018-058-11

PDF(417 KB)

Journal of Systems Science and Information ›› 2018, Vol. 6 ›› Issue (1) : 58-68. DOI: 10.21078/JSSI-2018-058-11

Research on Advertising and Pricing in E-Supply Chain Under Different Dominant Modes

Author information +

History +

Abstract

The E-supply chain is formed gradually along with the development of network, which is getting more attention among enterprises with unique advantages. Three E-supply chain operation modes are constructed in this paper, then the optimal pricing and advertising strategies under those modes are studied and compared, which are demonstrated with numerical examples. The results of comparison and analysis show that: Selling price, network platform service level, advertising investment and the profits of manufacturer, network platform and E-supply chain all increase with advertising effectiveness of stimulating demand growth. Under centralized decision-making mode, service level is highest, advertising investment is largest and the profit of E-supply chain is highest as well. When manufacturer leads decentralized decision-making mode, not only network service level, advertising investment and the profit of manufacturer can gain better results, but also profit of network platform can be higher while the advertisement effect of increasing demand is big enough. Additionally, it is confirmed that centralized decision-making is better than decentralized decision-making for system operation. Besides, decentralized decision-making mode led by manufacturer is superior to it led by network platform on the condition that advertisement effect is obvious.

Key words

E-supply chain / dominant mode / advertising strategy

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

Yuyan WANG , Zhaoqing YU. Research on Advertising and Pricing in E-Supply Chain Under Different Dominant Modes. Journal of Systems Science and Information, 2018, 6(1): 58-68 https://doi.org/10.21078/JSSI-2018-058-11

1 Introduction

The promotion of "Internet +" strategy makes it more low-cost and faster for producers to communicate with marketing. As more enterprises have begun to sell directly to consumers over the Internet, the E-supply chain composed of Internet and supply chain is formed and gets rapid development, such as JD.COM, TMALL.COM. It has been integrated into people's life, becoming an important way for enterprise to communicate with consumers, and successfully developing into a hot topic to which academic circles pay attention gradually.

A considerable number of articles have been written on E-supply chain in recent years. Chiang, et al.^[1] applied a game analysis on traditional channel and E-channel, and found that E-channel decreases wholesale price and coordination thereby can be realized. Thomas and Alt^[2] presented a supply chain management model of E-procurement system (EPS) and indirect product. Sherer^[3] elaborated on the notion of value network advocacy in supply chain management and indicates that many management information systems need to be more customer-focused and pay more attention to information flow. Iyer, et al.^[4] adopted "fit" concept and analysed the integration and performance of E-supply chain, which would decrease when product turbulence and demand unpredictability jointly increased. As for the practical application of E-supply chain, according to Valverde and Saade^[5], the fact that E-supply chain management has advantages in improving efficiency and increasing profits has been demonstrated by an illustration: The electronics manufacturing industry in North America. Lu and Liu^[6] mainly compared single-channel and dual-channel systems in a two-echelon supply chain, the study aimed at helping manufacturers decide whether or not to open an E-channel. Araneda, et al.^[7] addressed the coordination of capacities of two manufacturers in a B2B supply chain, and a contract that leads the two manufacturers to win-win capacity decisions was proposed and analyzed as well. Siddiqui and Raza^[8] investigated the status quo of E-supply chain research with a five-dimensional framework, finding that innovation, adoption and barriers receive significant attention in the earlier period, while in the latter period, the focus shifts to issues involving integration and collaboration. Kiselicki, et al.^[9] learned that several disadvantages characterizing the traditional model could potentially be solved through the E-supply chain model. All of these studies, however, do not address advertising problem——A key problem in E-supply chain. Due to lack of specialized entity sales organizations and sales network in E-supply chain, advertising becomes a main way for E-supply chain enterprises to expand product influence, and directly affects the enterprises' survival and development.

Previous advertising research mainly focus on traditional supply chain. Considering that demand is affected by advertising and price, Xie and Neyret^[10] built a traditional supply chain consisting of a manufacturer and a retailer and identified optimal advertising and pricing for supply chain enterprises. Much research on cooperative advertising are carried out especially in recent years. Ahmadi and Hoseinpour^[11] discussed equilibrium solution of centralized advertising in a two-stage supply chain under cooperative game and non-cooperative game. Aust and Buscher^[12] conducted a literature review to compare cooperative advertising strategy in traditional supply chain. Zhao, et al.^[13] analysed cooperative advertising decisions in a two-tier supply chain, and explicitly showed how demand price react to advertising decision. Considering the influence of the network marketing, Yan^[14] studied enterprises' centralized advertising and pricing strategy, the influence of advertising strategy on firm performance is examined in this paper as well. Then Yan, et al.^[15] studied manufacturer's centralized advertising and information sharing on the condition that demand is uncertain.

The above research achievements establish basis for us to study advertising in E-supply chain. This paper is going to research on advertising and pricing in E-supply chain under different dominant modes, which is of great significance to promoting and enhancing the development of E-supply chain.

2 The Instructions of Model

Assume a short-life-cycle product E-supply chain consisting of one manufacturer and one network platform whose overall structure is shown in Figure 1. In E-supply chain, without particular retailer, manufacturer is not only responsible for production, but also releases sales information with the help of network platform for product sales. While using the sales service from network, manufacturer also pays commission to network platform as compensation. Meanwhile, manufacturer and network platform would like to adopt advertising strategy to simulate sales.

Figure 1 Structure of the E-supply chain

Full size|PPT slide

Model assumptions and symbols are shown as follows:

p

: unit selling price;

c

: unit production cost by manufacturer;

q

: consumer demand;

ρ

: unit commission by network platform, also means fees paid to network platform by manufacturer for selling every unit product;

s

: network platform service level. Assume that demand increase with service level;

v

: advertising investment;

q

is demand function quoted from [16], that is,

q = α - β p + γ \sqrt{s} + δ \sqrt{v} .

(1)

The parameters

α, β, γ, δ

are positive,

α

denotes market saturation. The parameters

β

γ

and

δ

denote price elastic coefficient, service level elastic coefficient and advertising investment elastic coefficient, respectively. They manifest the degree of selling price, service level and advertising investment in stimulating demand.

In order to ensure that these problems make sense, parameters in assumption models have to meet,

α - β c > 0, 4 β - δ^{2} - γ^{2} > 0.

The corresponding dominant modes vary with strength of manufacturer and network platform in E-supply chain. If manufacturer's strength is greater than the strength of network platform, manufacturer can seize chain's initiative and consequently become the dominant enterprise. On the contrary, when the strength of network platform is greater than that of manufacturer, network platform can dominate the chain. Therefore, there are two dominant modes in E-supply chain based on the difference of enterprise strength, namely, decentralized decision-making mode of manufacturer dominating and decentralized decision-making mode of network platform dominating. Besides, because of funds limitation the weaker subordinate enterprise is not likely to adopt advertising strategy, the powerful dominant enterprise generally bears advertising investment in E-supply chain. In the following sections, advertising and pricing in E-supply chain under different dominant modes are analyzed based on advertising investment subject.

3 Decentralized Decision-Making Mode

As independent economic agents, manufacturer and network platform both maximize their own profits as the goal of decision-making under decentralized decision-making mode. According to different dominant modes of E-supply chain, the corresponding dominant modes of decentralized decision-making are discussed in the following section.

3.1 Decentralized Decision-Making Mode of Manufacturer Dominating

If manufacturer dominates system, manufacturer's strength is stronger. In order to further expand sales market, manufacturer would employ advertising strategy and adequately advertise product. In this case, manufacturer's profit function is

π_{m} = (p - ρ - c) q - v .

(2)

For network platform, similarly, the profit function can be expressed as follows:

π_{e} = ρ q - s .

(3)

Under this decision-making mode, the relationship between the manufacturer and network platform is modeled as Stackelberg model with manufacturer as the leader and network platform as the follower. The sequential decision order can be described as follow: Manufacturer, as the leader, first declares selling price and advertising expenditure that he is willing to invest on the basis of market prediction. Network platform, as the follower, then sets its own service level. The equilibrium solutions are gained through backward induction.

Conclusion 1 Under decentralized decision-making mode of manufacturer dominating, we can obtain the optimal results as shown below:

The optimal selling price is

p^{1 *} = \frac{2 α + 2 β c + 2 β ρ + ρ γ^{2} - ρ δ^{2} - c δ^{2}}{4 β - δ^{2}} .

The optimal advertising investment is

v^{1 *} = \frac{δ^{2} (2 α + ρ γ^{2} - 2 β c - 2 β ρ)^{2}}{4 (4 β - δ^{2})^{2}} .

The optimal network platform service level is

s^{1 *} = \frac{ρ^{2} γ^{2}}{4} .

The optimal profits of manufacturer, network platform and the whole E-supply chain can be expressed respectively:

\begin{array}{rcl} π_{m}^{1 *} = \frac{(2 α - 2 β c - 2 β ρ + ρ γ^{2})^{2}}{4 (4 β - 4 δ^{2})}, \\ π_{e}^{1 *} = \frac{ρ (8 α β - 8 β^{2} c - 8 β^{2} ρ + ρ δ^{2} γ^{2})}{4 (4 β - δ^{2})}, \\ π^{1 *} = \frac{4 α^{2} + 4 β^{2} c^{2} - 4 β^{2} ρ^{2} + ρ^{2} γ^{4} - 4 β ρ^{2} γ^{2} - 8 α β c + 4 α ρ γ^{2} + ρ^{2} δ^{2} γ^{2} - 4 β c ρ γ^{2}}{4 (4 β - δ^{2})} . \end{array}

3.2 Decentralized Decision-Making Mode of Network Platform Dominating

If network platform dominates system, network platform's strength is stronger. So network platform would employ advertising strategy and spend money on advertising. Thus, the manufacturer's profit function is

π_{m} = (p - ρ - c) q .

(4)

Then the profit function of network platform is

π_{e} = ρ q - s - v .

(5)

In this part, we model the relationship between the manufacturer and network platform as Stackelberg model in the same way as in Part 3.1, while network platform being the leader and manufacturer being the follower. The sequential decision order can be described as follow: Firstly, network platform determines service level and advertising investment, then manufacturer presents selling price. We use backward induction to get the following equilibrium solutions.

Conclusion 2 Under decentralized decision-making mode of network platform dominating, we can obtain the optimal results as shown below:

The optimal selling price is

p^{2 *} = \frac{4 α + 4 β (c + ρ) + ρ (δ^{2} + γ^{2})}{8 β} .

The optimal advertising investment is

v^{2 *} = \frac{ρ^{2} δ^{2}}{16} .

The optimal network platform service level is

s^{2 *} = \frac{ρ^{2} γ^{2}}{16} .

The optimal profits of manufacturer, network platform and the whole E-supply chain can be expressed respectively:

\begin{array}{rcl} π_{m}^{2 *} = \frac{{[4 α - 4 β (c + ρ) + ρ (δ^{2} + γ^{2})]}^{2}}{64 β}, \\ π_{e}^{2 *} = \frac{ρ [8 α - 8 β (c + ρ) + ρ (δ^{2} + γ^{2})]}{16}, \\ π^{2 *} = π_{m}^{2 *} + π_{e}^{2 *} = \frac{{[4 α - 4 β (c + ρ) + ρ (δ^{2} + γ^{2})]}^{2} + 4 β ρ [8 α - 8 β (c + ρ) + ρ (δ^{2} + γ^{2})]}{64 β} . \end{array}

4 Centralized Decision-Making Mode

Centralized decision-making mode is an ideal state for E-supply chain, under which manufacturer and network platform cooperate with advertising strategy and share advertising costs together. That is to say, both manufacturer and network platform maximize E-supply chain's profit when making decisions, which also indicates that the dominant positions are consistent. Hence, E-supply chain's profit function is

π = (p - c) q - v - s .

(6)

Only when manufacturer and network platform determine selling price, advertising investment, service level together, E-supply chain can achieve profit maximization. The objective function can be rewritten as

max_{p, v, s} π = (p - c) q - v - s .

(7)

By taking

\partial π / \partial p = 0, \partial π / \partial s = 0, \partial π / \partial v = 0

, we obtain the optimal results.

Conclusion 3 Under centralized decision-making mode, we can obtain the optimal results as shown below:

The optimal selling price is

p^{3 *} = \frac{2 α + 2 β c - (δ^{2} + γ^{2}) c}{4 β - δ^{2} - γ^{2}} .

The optimal advertising investment is

v^{3 *} = \frac{δ^{2} (α - β c)^{2}}{(4 β - δ^{2} - γ^{2})^{2}} .

The optimal network platform service level is

s^{3 *} = \frac{γ^{2} (α - β c)^{2}}{(4 β - δ^{2} - γ^{2})^{2}} .

The profit of E-supply chain is

π^{3 *} = \frac{(α - β c)^{2}}{4 β - δ^{2} - γ^{2}} .

5 Comparisons

According to comparison with above conclusions, further relationship of optimal decision variables are analyzed respectively.

Conclusion 4 The selling price have

p^{1 *} > p^{2 *}

When

δ < δ_{1}

p^{1 *} > p^{3 *}

; when

δ > δ_{1}

p^{1 *} < p^{3 *}

, where

δ_{1} = \sqrt{2 β - \frac{γ^{2} (2 α - 2 β c - 2 β ρ + ρ γ^{2})}{ρ (4 β - δ^{2})}} .

Proof See in Appendix 1.

From Conclusion 4, we can know: It is obvious that under decentralized decision-making mode, when manufacturer dominates E-supply chain, with absolute control over system, the selling price is higher compared to network platform dominating E-supply chain. Also, under centralized decision-making mode, selling price is higher than it under decentralized decision-making mode in the case of

δ > δ_{1}

. This is because manufacturer and network platform bear advertising expenditure together under centralized decision-making mode, increased cost due to increased advertising investment makes selling price rise to guarantee the system's profit. However, if

δ < δ_{1}

, selling price in centralized decision-making mode is lower than it in decentralized decision-making mode.

Conclusion 5 Advertising investment have:

v^{3 *} > v^{1 *} > v^{2 *} .

Proof See in Appendix 2.

Conclusion 5 indicates that advertising investment is highest in centralized decision-making mode thanks to co-op advertising. Manufacturer invests more in advertisement than network platform in decentralized decision-making mode, which reveals that manufacturer is more focused on advertising to increase demand. Thus, if manufacturer's strength is strong enough, manufacturer is likely to put more money in advertising compared with network platform.

Conclusion 6 Network platform service level have

s^{2 *} = \frac{1}{4} s^{1 *}, s^{3 *} > s^{1 *} > s^{2 *} .

Proof See in Appendix 3.

As we can see from Conclusion 6, also combining with Conclusions 1 to 3, network platform service level is merely related to commission and the elasticity coefficient of service level in stimulating demand in decentralized decision-making mode. Under the circumstance that manufacturer and network platform make decision together, highest service level is achieved. And obviously, service level is higher when manufacturer dominates E-supply chain, especially compared with service level when network platform occupies dominant position. One interpretation may be that if network platform dominates system, relying on its own dominance, it would lower service level to reduce costs and guarantee profit.

Conclusion 7 1) Manufacturer's profit have

π_{m}^{1 *} > π_{m}^{2 *};

2) E-supply chain's profit have

π^{3 *} > π^{1 *} > π^{2 *} .

Proof See in Appendix 4.

Conclusion 7 illustrates the profit functions. When manufacturer dominates E-supply chain in decentralized decision-making mode, manufacturer is most profitable. And E-supply chain achieve highest optimal profit in centralized decision-making mode. Therefore, we could say that it is when enterprises of E-supply chain occupy equal dominant position and make collaborative decisions that the system can achieve best operation performance.

6 Numerical Analysis

While our conclusions can be derived analytically, the analytical denotes are too abstract to provide practical significance. So now we use numerical examples to demonstrate the effect of change of

δ

Assume

α = 100, β = 15, c = 3, m = 2, γ = 4

δ

is independent variable and

δ \in [1, 5]

. We draw all decision variable curves with the change of

δ

in Figures 2~7.

Figures show that:

1) Selling price, network platform service level, advertising investment and the profits of manufacturer, network platform and E-supply chain are positively related to

δ

, advertising investment elastic coefficient in stimulating demand. In other words, they all increase with advertising effectiveness of boosting demand.

2) The highest service level, the largest advertising investment, the maximal E-supply chain profit are provided under centralized decision-making mode. And it is quite clear that selling price relates to

δ

. When

δ

reaches a certain degree (

δ > B

in Figure 2), the highest selling price is observed in centralized mode, which confirms that high advertising effectiveness of boosting demand is beneficial to E-supply chain operation.

3) Decentralized decision-making mode of manufacturer dominating provides higher service level, more advertising investment and higher manufacturer profit in comparison with decentralized decision-making mode of network platform dominating, which also implies that who owns control over E-supply chain can increase own profit. And similarly, profit of network platform is closely related to

δ

. Only when

δ

reaches a certain degree (

δ > D

in Figure 6) can the profit of network platform be higher. The results further reflects that if advertising effectiveness is large, the chances are much more that decentralized decision-making mode of manufacturer dominating are explicitly favored by manufacturer and network platform.

Thus it can be seen that centralized decision-making is always better than decentralized decision-making for system operation. However, centralized decision-making is an ideal state, which requires coordination mechanism to be realized. When the system lacks effective coordination mechanism, and if advertisement effect is big, decentralized decision-making mode of manufacturer dominating is an ideal choice for E-supply chain enterprises.

7 Concluding remarks

An E-supply chain model composed of one manufacturer and one network platform is constructed in this paper, and three E-supply chain operation modes are analyzed, including "decentralized decision-making mode of manufacturer dominating", "decentralized decision-making mode of network platform dominating", "centralized decision-making mode". Selling price, advertising investment and service level are calculated for all cases, respectively. Then comparisons are made and numerical examples are analyzed to verify conclusions. The results show that:

1) Selling price, network platform service level, advertising investment and the profits of manufacturer, network platform and E-supply chain all increase with advertising effectiveness of stimulating demand growth.

2) Under centralized decision-making mode, service level is highest, advertising investment is largest and the profit of E-supply chain is highest as well.

3) Under decentralized decision-making mode, when manufacturer leading E-supply chain, higher service level, more advertising investment and higher manufacturer profit are gained in comparison with decentralized decision mode of network platform dominating. But if advertising effectiveness reaches a certain degree, network platform's profit can be higher in case of platform dominating E-supply chain.

4) Centralized decision-making is absolutely better than decentralized decision-making for system operation if coordination mechanism is achieved. But if system lacks effective coordination mechanism and when the advertisement effect is big, decentralized decision-making mode led by manufacturer is an practical choice for E-supply chain enterprises.

Actually, the article only studies decision-making problem in E-supply chain under different dominant modes. As a result, the coordination of different dominant modes, especially coordination between centralized decision-making and decentralized decision-making will be future research direction.

Appendix

Appendix 1 Proof of Conclusion 4

Comparing the optimal selling price of Parts 3.1 and 3.2, we can get

p^{1 *} - p^{2 *} = \frac{4 δ^{2} (α - β c) + ρ [4 β γ^{2} - 8 β δ^{2} + δ^{2} γ^{2} + δ^{4}]}{8 β (4 β - δ^{2})},

which can be rewritten as

p^{1 *} - p^{2 *} = \frac{4 δ^{2} (α - β c - 2 β ρ) + ρ [γ^{2} (4 β - δ^{2} - γ^{2}) + (γ^{2} + δ^{2})^{2}]}{8 β (4 β - δ^{2})} .

By the known,

α - β c > 0

α

denotes market saturation, big positive number. So it's easy to prove

p^{1 *} - p^{2 *} > 0

Then compare

p^{1 *}

and

p^{3 *}

\begin{array}{rcl} p^{1 *} - p^{3 *} & = & \frac{- 2 γ^{2} (α - β c) + ρ [8 β^{2} - γ^{4} + δ^{4} + 2 β (γ^{2} - 3 δ^{2})]}{(4 β - δ^{2}) (4 β - δ^{2} - γ^{2})} \\ = & \frac{- γ^{2} (2 α - 2 β c - 2 β ρ + ρ γ^{2}) + ρ (4 β - δ^{2}) (2 β - δ^{2})}{(4 β - δ^{2}) (4 β - δ^{2} - γ^{2})} . \end{array}

By solving

p^{1 *} = p^{3 *}

, we can get critical value

δ_{1} = \sqrt{2 β - \frac{γ^{2} (2 α - 2 β c - 2 β ρ + ρ γ^{2})}{ρ (4 β - δ^{2})}},

which is point B in Figure 2.

Therefore, by means of solving process of

δ_{1}

, we can compare

p^{2 *}

and

p^{3 *}

to get the other critical value

δ_{2}

p^{3 *} - p^{2 *} = \frac{(4 α - 4 β c) (δ^{2} + γ^{2}) - ρ (4 β - δ^{2} - γ^{2}) (4 β + δ^{2} + γ^{2})}{8 β (4 β - δ^{2} - γ^{2})} .

Let

p^{3 *} = p^{2 *}

, we have

δ_{2} = \sqrt{4 β - γ^{2} - \frac{(4 α - 4 β c) (δ^{2} + γ^{2})}{ρ (4 β + δ^{2} + γ^{2})}} .

Appendix 2 Proof of Conclusion 5

v^{2 *} - v^{1 *} = \frac{δ^{2} [ρ (4 β - δ^{2}) + 2 (2 α + ρ γ^{2} - 2 β c - 2 β ρ)] [ρ (4 β - δ^{2}) - 2 (2 α + ρ γ^{2} - 2 β c - 2 β ρ)]}{16 (4 β - δ^{2})^{2}} .

By the known,

α - β c > 0

α

denotes market saturation, big positive number, then

ρ (4 β - δ^{2}) - 2 (2 α + ρ γ^{2} - 2 β c - 2 β ρ) < 0.

As a result,

v^{2 *} - v^{1 *} < 0

, that is,

v^{1 *} > v^{2 *}

\begin{array}{rcl} v^{3 *} - v^{1 *} = \frac{δ^{2} [2 (4 β - δ^{2}) (α - β c) + (4 β - δ^{2} - γ^{2}) (2 α + ρ γ^{2} - 2 β c - 2 β ρ)]}{4 (4 β - δ^{2})^{2} {(4 β - δ^{2} - γ^{2})}^{2}} \\ \cdot [2 (4 β - δ^{2}) (α - β c) - (4 β - δ^{2} - γ^{2}) (2 α + ρ γ^{2} - 2 β c - 2 β ρ)] . \end{array}

Just like the proof process of

v^{1 *} > v^{2 *}

, it is obvious to get the conclusion of

v^{3 *} > v^{1 *}

Appendix 3 Proof of Conclusion 6

\begin{array}{rcl} s^{2 *} = \frac{ρ^{2} γ^{2}}{16} = \frac{1}{4} s^{1 *}, \\ s^{1 *} - s^{3 *} = \frac{γ^{2} [ρ (4 β - δ^{2} - γ^{2}) + 2 (α - β c)] [ρ (4 β - δ^{2} - γ^{2}) - 2 (α - β c)]}{4 {(4 β - δ^{2} - γ^{2})}^{2}} . \end{array}

By the known, it's easy to prove

s^{1 *} - s^{3 *} < 0

, namely

s^{3 *} > s^{1 *}

Appendix 4 Proof of Conclusion 7

\begin{array}{rcl} π_{m}^{1 *} - π_{m}^{2 *} = \frac{4 β ρ (8 α - 8 β c - 8 β ρ + 3 ρ γ^{2} + ρ δ^{2}) (γ^{2} - δ^{2}) + (4 α - 4 β c - 4 β ρ + ρ γ^{2} + ρ δ^{2})^{2} δ^{2}}{64 β (4 β - 4 δ^{2})} > 0, \\ π_{e}^{1 *} - π_{e}^{2 *} = \frac{ρ (8 α δ^{2} + ρ δ^{4} + 5 ρ δ^{2} γ^{2} - 8 β c δ^{2} - 12 β ρ δ^{2} - 4 β ρ γ^{2})}{16 (4 β - δ^{2})} \\ = \frac{ρ [δ^{2} (8 α - 8 β c - 8 β ρ + ρ δ^{2} + ρ γ^{2}) + 4 ρ (δ^{2} γ^{2} - β δ^{2} - β γ^{2})]}{16 (4 β - δ^{2})} . \end{array}

If advertising investment elastic coefficient is small enough,

π_{e}^{1 *} < π_{e}^{2 *}

will be obtained. However, as advertising investment elastic coefficient increases, the relationship between

π_{e}^{1 *}

and

π_{e}^{2 *}

turns out just the opposite. Considering

π_{m}^{1 *} > π_{m}^{2 *}

, it is easy to prove

π^{1 *} > π^{2 *}

References

Publishing order | Descend order by publishing year | Descend order by cited within

1	Chiang W Y K, Chhajed D, Hess J D. Direct marketing, indirect profits: A strategic analysis of dual-channel supply-chain design. IIE Transactions, 2005, 37 (5): 407- 427. https://doi.org/10.1080/07408170590885594 Cited in this article [1]

2	Thomas P, Alt R. Successful use of e-procurement in supply chains. Supply Chain Management: An International Journal, 2005, 10 (2): 122- 133. https://doi.org/10.1108/13598540510589197 Cited in this article [1]

3	Sherer S A. From supply-chain management to value network advocacy: Implications for E-Supply Chains. Supply Chain Management: An International Journal, 2005, 10 (2): 77- 83. https://doi.org/10.1108/13598540510589151 Cited in this article [1]

4	Iyer K N S, Germain R, Claycomb C. B2B e-commerce supply chain integration and performance: A contingency fit perspective on the role of environment. Information & Management, 2009, 46 (6): 313- 322. https://doi.org/10.3969/j.issn.1001-9960.2009.06.271 Cited in this article [1]

5	Valverde R, Saade R G. The effect of E-supply chain management systems in the North American electronic manufacturing services industry. Journal of theoretical and applied electronic commerce research, 2015, 10 (1): 79- 98. https://doi.org/10.4067/S0718-18762015000100007 Cited in this article [1]

6	Lu Q, Liu N. Effects of e-commerce channel entry in a two-echelon supply chain: A comparative analysis of single- and dual-channel distribution systems. International Journal of Production Economics, 2015, 165, 100- 111. https://doi.org/10.1016/j.ijpe.2015.03.001 Cited in this article [1]

7	Araneda F C, Lustosa L J, Minner S. A contract for coordinating capacity decisions in a business-to-business (B2B) supply chain. International Journal of Production Economics, 2015, 165, 158- 171. https://doi.org/10.1016/j.ijpe.2015.03.016 Cited in this article [1]

8	Siddiqui A W, Raza S A. Electronic supply chains: Status & perspective. Computers & Industrial Engineering, 2015, 88, 536- 556. https://doi.org/10.3969/j.issn.1001-3695.2015.02.048 Cited in this article [1]

9	Kiselicki M, Josimovski S, Joncheski L. Implementation of internet technologies in the supply chain of SEMs in macedonia. Journal of Sustainable Development, 2015, 5 (13): 69- 87. Cited in this article [1]

10	Xie J, Neyret A. Co-op advertising and pricing models in manufacturer-retailer supply chains. Computers & Industrial Engineering, 2009, 56 (4): 1375- 1385. Cited in this article [1]

11	Ahmadi A, Hoseinpour P. On a centralized advertising model for a supply chain with one manufacturer and one retailer. European Journal of Operational Research, 2012, 219 (2): 458- 466. https://doi.org/10.1016/j.ejor.2011.06.032 Cited in this article [1]

12	Aust G, Buscher U. Cooperative advertising models in supply chain management: A review. European Journal of Operational Research, 2014, 234 (1): 1- 14. https://doi.org/10.1016/j.ejor.2013.08.010 Cited in this article [1]

13	Zhao L, Zhang J, Xie J. Impact of demand price elasticity on advantages of centralized advertising in a two-tier supply chain. International Journal of Production Research, 2016, 54 (9): 2541- 2551. https://doi.org/10.1080/00207543.2015.1096978 Cited in this article [1]

14	Yan R. Centralized advertising, pricing strategy and firm performance in the e-marketing age. Journal of the Academy of Marketing Science, 2010, 38 (4): 510- 519. https://doi.org/10.1007/s11747-009-0171-z Cited in this article [1]

15	Yan R, Cao Z, Pei Z. Manufacturer's centralized advertising, demand uncertainty, and information sharing. Journal of Business Research, 2016, 69 (2): 709- 717. https://doi.org/10.1016/j.jbusres.2015.08.011 Cited in this article [1]

16	Wang Y Y. Research on advertising coordination mechanism in direct marketing closed-loop supply chain (in chain). Journal of Industrial Engineering and Engineering Management, 2013, 27 (4): 205- 213. Cited in this article [1]

Acknowledgements

The authors gratefully acknowledge the Editor and anonymous referees for their insightful comments and helpful suggestions that led to a marked improvement of the article.

Funding

the National Natural Science Foundation of China(71501111)

the Natural Science Foundation of Shandong Province(ZR2014JL046)

PDF(417 KB)

300

Accesses

Citation

Detail

Sections

Recommended

Received	Accepted	Published
2017-02-24	2017-06-20	2018-02-25
Issue Date
2018-02-25

Please choose a citation manager

Content to export

Abstract

Key words

Cite this article

1 Introduction

2 The Instructions of Model

Figure 1 Structure of the E-supply chain

3 Decentralized Decision-Making Mode

3.1 Decentralized Decision-Making Mode of Manufacturer Dominating

3.2 Decentralized Decision-Making Mode of Network Platform Dominating

4 Centralized Decision-Making Mode

5 Comparisons

6 Numerical Analysis

Figure 2 Selling price curves

Figure 3 Service level curves

Figure 4 Advertising investment curves

Figure 5 Manufacturer' s profit curves

Figure 6 Network platform's profit curves

Figure 7 E-supply chain's profit curves

7 Concluding remarks

Appendix

{{custom_sec.title}}

{{custom_sec.title}}

References

{{custom_fnGroup.title_en}}

Footnotes

Acknowledgements

{{custom_ack.title_en}}

Funding

Share

模态框（Modal）标题

Please choose a citation manager

Content to export

Abstract

Key words

Cite this article

1 Introduction

2 The Instructions of Model

Figure 1 Structure of the E-supply chain

3 Decentralized Decision-Making Mode

3.1 Decentralized Decision-Making Mode of Manufacturer Dominating

3.2 Decentralized Decision-Making Mode of Network Platform Dominating

4 Centralized Decision-Making Mode

5 Comparisons

6 Numerical Analysis

Figure 2 Selling price curves

Figure 3 Service level curves

Figure 4 Advertising investment curves

Figure 5 Manufacturer' s profit curves

Figure 6 Network platform's profit curves

Figure 7 E-supply chain's profit curves

7 Concluding remarks

Appendix

{{custom_sec.title}}

{{custom_sec.title}}

References

{{custom_fnGroup.title_en}}

Footnotes

Acknowledgements

{{custom_ack.title_en}}

Funding