• No results found

Decision Analysis of Conditional Risk Method Based on Accounts Receivable Financing Mode

N/A
N/A
Protected

Academic year: 2020

Share "Decision Analysis of Conditional Risk Method Based on Accounts Receivable Financing Mode"

Copied!
5
0
0

Loading.... (view fulltext now)

Full text

(1)

2018 International Conference on Computer, Communication and Network Technology (CCNT 2018) ISBN: 978-1-60595-561-2

Decision Analysis of Conditional Risk Method Based on Accounts

Receivable Financing Mode

Guang-ming ZHANG and Yu BAO

Jiangsu university of science and technology, China

Keywords: Capital flow of supply chain, Conditional value-at-risk, Default risk, Optimal rate.

Abstract. In order to study how factoring mode is involved in easing the flow of funds in the supply chain, such as upstream and downstream enterprises, etc. On the basis of accounts receivable financing mode, we use the measurement criteria of conditional risk method to formulate decision criteria. Then, it is assumed that the market demand will fluctuate randomly and consider the default risk of the downstream enterprises, and establish a conditional risk model consisting of three parties of a single factoring, a single retailer and a single product supplier. After balancing the pros and cons, we get the optimal rate of factoring, the optimal ordering quantity of retailers and the optimal wholesale price of product suppliers. The results show that under certain conditions, the use of factoring model can make the three parties optimize the operation of funds under the premise of effectively avoiding the risk, and all achieve the best goal.

Introduction

As we all know, if a supply chain wants to gain advantages in the market competition, the running of capital flow in the supply chain must be safe and smooth.otherwise, the supply chain is broken, which endangers the operation of the whole supply chain.In our country, the demand of small and medium-sized enterprises can not be satisfied because of their lack of funds and the inability to increase production.

Establishment and Analysis of CVaR Model Based on Accounts Receivable Factoring Mode

Symbolic Definition

The symbol hypothesis and the name of the variable are as follows:

Q:Retailer's order quantity; P: Market price of products;

W:Wholesale price of products; C:Production cost of unit product,C<W<P;

x:market demand,X is a random variable with a random distribution, which satisfies the distribution function

(x)

F and probability density functionf(x);

B: Unit repurchase price; r: Factoring interest rate; a:Unit guarantee amount; Z:Unit penalty,ifZ = k a,0 < k <1;

y: Treatment of surplus value of factoring merchants,if y+ <a W(1+r);

1

α :Risk aversion coefficient of retailer;

2

α :Risk aversion coefficient of supplier; α3:Risk aversion coefficient of factoring; β:Return threshold; c1:Production cost of supplier unit;

2

c:Factoring rate;

1

m:Intermediary fees charged by a factoring

agent to the retailer;

2

m :Intermediary fees charged by a factoring provider; ϕ:Probability of breach of contract

Premise Hypothesis and Problem Analysis

Hypothesis 1: The supplier only produces one product. In the early stage of production, if the supplier is short of funds, it can be produced from outside financing through factoring mode. Suppose that the total amount of financing from suppliers to factoring is R=QW, and there is no Retention Fund.All the money for financing is used to produce products.

(2)

process, small and medium-sized suppliers often have sufficient orders and insufficient production funds and need to finance outside. At this point, retailers need to guarantee because of insufficient credit loans.The retailer will bear a penalty amount of Z for breach of contract, and the factoring provider will provide the guarantee amount for the manufacturer to reduce the risk, that is, the factoring ratio should be adjusted.In order to avoid risks, suppliers sign an optimal order contract with retailers.Finally, after factoring determines the financing rate, the supplier and the retailer determine the wholesale price and the order quantity respectively.In this paper, the risk aversion level of three parties in the supply chain is considered, and the CVaR model of the supplier, retailer and factoring provider is established respectively, and the optimal solution of the supply chain scheme will be solved.

Revenue Function Analysis of Retailers, Suppliers and Factoring Firms

When Q > x,the order quantity of retailers exceeded the market demand, resulting in a large number of surplus, which caused retailers to be unable to repay. Retailers tend to default and pay penalty costs at this time.

Retailer's profit function: ω =r1 Px QW− (1 + −r) B(Q−x);ωr2= −ka(Q−x)+x P( −W(1+r)) Supplier's profit function: ωs1=(W−c Q B1) − (Q )−x;ω =−s2 a(1−k)(Q )−x+Q(Wc1)

Factoring agency's profit function:;

1 1 2 2

b m m Qc QrW

ω

= + − +

ω

b2

= + +

m

1

m y

2

(Q x)

− +

Wx

(1 ) (Q x)

+ +

r

a

− −

QW c

(

+

2

)

When Q < x,the supply of goods was in short supply and retailers were unlikely to default. Retailer's profit function: ωr3= −W(1 + +r) PQ

Supplier's profit function: ωs3 =Q(W−c1)

Factoring agency’s profit function:ωb3=m1+m2−Qc2+QrW

The CVaR Model of Retailers, Suppliers and Factmakers

First, the auxiliary function is introduced:

1 0

1 1

( ) ( ) (x)

F β β β ω f dx

α

+∞

= − − +

,This article takes into account the benefits of different situations.

When Q >x, The case of breach of contract appears, we bring in

2

r

ω

r3:

Retailer's CVaR model:

1

0 1 1

(Q, ) [ ( (P (1 ) ) (Q )) (x) ( (P ( )

1 1 ) (x) ]

Q r

Q

F β β Wx r ka x f dx WQ r f dx

α β β

+∞

+ −

= − − − + + − +

+

− +

Supplier's CVaR model:

1 1

2 0

1

(W ) a 1

(W, ) [ ( (Q x)(1 ) (x) ( (W c )) (x)

1 ]

s

Q Q

F β β Q c k f dx β Q f dx

α β

+∞

= − − − + − + + − − +

Factoring agency’s CVaR model:

1 2 1

3 0

2 1

1 (Q ) (1 ) a(Q x)

(r, ) [ ( Q(W c ) ) (x) ( (W c )) (x)

1 ]

b

Q Q

F β β β y x Wx r m m f dx β rQW f dx

α

+∞

= − − − − + − − + + − − + + − − +

When Q < x , The case of breach of contract appears,we bring in

1

r

ω

r3:

Retailer's CVaR model:

2 0

1

1

(Q, ) [ ( (1 ) ( ) ) (x) ( (P ( )

1 1 ) (x) ]

Q r

Q

F β β β QW r Px B Q x f dx β WQ r f dx

α

+∞

= − + − − − +

+ + +

− − +

Supplier's CVaR model:

2 0

2 (W 1) (Q x) ( (W c ))1

1

(W, ) [ ( (x) (x) ]

1 s

Q Q

F β β β Q c B f dx β Q f dx

α

+∞

= − − − + − + + − − +

Factoring agency’s CVaR model:

0

2 2 1 2

3

1

(r, ) [ ( ) (x ]

1 )

Q b

F β β β r Q W c Q m m f d x

α

= − − + − − +

(3)

Decision Optimization of Retailers, Suppliers and Factoring Based on CVaR

Retailer's Optimal Order Quantity. Theorem 1:Supplier wholesale prices and factoring interest rates are known,whenQ <x ,which means the retailer will not default.Retailers seek maximum profits

while considering risk aversion.

Because of Fr2(Q , β)is monotonically decreasing, there is no optimal solution. Therefore, the

result of solving equation is:

only if βr2= −Q W[ (1+ +r) P],Retailers have an optimal order:

1 2

(1 )( (1 ))

( )

r

P W r

Q

Z P B α

− − +

=

− Theorem 2 can be obtained by the same way.

Theorem 2:Supplier wholesale prices and factoring interest rates are known, when Q >x ,which means the retailer will not default. Retailers seek maximum profits while considering risk aversion.

the result of solving equation is that Retailers have an optimal order: 1 1

(1 )( (1 ))

[ (1 ) ]

r

P W r

Q

Z P W r ka

α

− − +

=

− + +

Supplier's Optimal Wholesale Price. Theorem 3: If optimal order of retailer is

* 1

2

(1 ) ( (1 ) )

( )

r

P W r

Q

Z P B

α

− − +

=

− , when 1

(Q) 1 0 1 F α − > − ,

Suppliers seek maximum profits while considering risk aversion. the result of solving equation is that supplier's optimal wholesale price is:

* 1 1 1

2

2 1

B P (1 ) c ( ) (1 )

( P B ) (1 ) B (1 ) (1 )

s P B W r α α α α − + − − = − − + − +

Theorem 4 can be obtained by the same way.

Theorem 4: If optimal order of retailer is * 1 1

(1 ) ( (1 ) )

[ (1 ) ]

r

P W r

Q

Z P W r k a

α

− − +

=

− + + ,when 1

(Q) 1 0 1 F α − > −

Suppliers seek maximum profits while considering risk aversion. the result of solving equation is that supplier's optimal wholesale price is:

* 1 2 1

1

2

a(1 k)(1 )(1 r) (1 )(P c (1 ) ka) 2(1 r)(1 )

s

r

W α α

α

− − + + − + + +

=

+ −

Factoring Agency’S Optimal Interest Rate. Theorem 5: If the optimal order of retailer

is * 1

2

(1 ) ( (1 ) )

( )

r

P W r

Q

Z P B

α

− − +

=

− ,supplier's optimal wholesale price is:

* 1 1 1

2

2 1

B P (1 ) c ( ) (1 )

( P B ) (1 ) B (1 ) (1 )

s P B W r α α α α − + − − =

− − + − + ,After the calculation,I get that:

If the factoring firm has the best interest rate r*b2 , There must be

* *

* 2 2 *

2 2 2

W

(W s ) r (W ) 0

s s

Q

Q r r c

r r

∂ ∂

+ + − =

∂ ∂ and

/

2

2Bf(Q)+ f (Q)(P Br)+ ( c +rW)<0

Theorem 6: If the optimal order of retailer is * 1 1

(1 )( (1 )) [ (1 ) ] r

P W r

Q

Z P W r k a

α

− − +

=

− + + ,supplier's optimal

wholesale price is: *1 1 2 1

2

a(1 k)(1 )(1 r) (1 )(P c (1 ) ka) 2(1 r)(1 )

s

r

W α α

α

− − + + − + + +

=

+ − ,After the calculation,I get that:

(1)If 3 ( ) 1 0 (1 ) F Q α − ≤

− ,Fb1(r, β)<0, 2 * 1 2 0 r Q r ∂ <

∂ and

3

1

0 (x) 0

Z xf dx

α −

>

,there will be sufficient and

necessary conditions : 1 2

2 2 (r, )

0 b F r β ∂ <

∂ , The best interest rate 1*

2 b

r can be obtained by the factoring

agent. (2) If 3 ( ) 1 0 (1 ) F Q α − > − ,

/(q) 0

f > , there will be sufficient and necessary conditions : 2 2 2 1 (r, ) 0 b F r β ∂ < ∂ ,

The best interest rate 2* 2

b

r can be obtained by the factoring agent.

Literature References

(4)

the problem of low supply chain efficiency can not be effectively solved[1].It is this big environment that has spawned supply chain finance.

Supply chain finance is not something new.As early as 2003, James B.Rice[2], a foreign scholar, defined the concept of early supply chain finance.He proposed that we could try to apply traditional financial instruments to the operation of supply chain, and effectively enhance the efficiency of production and operation of enterprises in the supply chain.Holfman. E[3] put forward a similar view.He believes that supply chain finance can improve the management efficiency of the whole supply chain and the net income of the whole society by regulating the flow of funds between upstream and downstream enterprises through commercial banks.Yue-fei Hu[4], a domestic scholar, further points out that The supply chain finance, that is, the financial institution represented by the bank, provides a better fund operation scheme to the upstream and downstream enterprises of the supply chain to achieve the purpose of integrating all the resources in the supply chain. He puts forward a new concept of the evolution from the "financial supply chain" to the supply chain finance.

As one of the supply chain financial products, the account receivable factoring model is widely used internationally because of its advantages of convenient operation mode, low cost of financing and so on.This paper mainly studies the application of factoring mode in the supply chain, drawing on the experience of many domestic and foreign scholars. Sopranzetti[5] set up a supplier profit model to study the supplier's factoring strategy. It believes that both the bankruptcy risk and the credit level will affect the willingness of the enterprise to take the right of recourse.Leora Klapper [6] analyzed the advantages and challenges of accounts receivable factoring financing, and put forward the concept of reverse factoring.Hui yu [7] have studied the influence of the operation process and financing mode on the performance of supply chain.

In addition, CVaR has been widely applied to supply chain research in recent years because of its unique advantages in the field of financial risk control.For example, Yan-Ju Zhou[8] constructed a multi product ordering risk decision model through CVaR method.C B Zhu[9] has studied how to use the CVaR rule to optimize the coordination mechanism and supply chain decision-making under the condition of the supply chain terminal.C B Zhong[10] used CVaR rule to coordinate the revenue sharing model of the supply chain.

It is undeniable that the research results have played a great role in promoting the development of supply chain management and risk control, but the lack of the United States and China are not fully considered when most scholars have studied the related issues.For example, the distinction between financing methods is not prominent, the risk attitude is not fully considered and the participants in the supply chain are not fully considered.Therefore, this article only analyses the mode of accounts receivable factoring, and establishes a conditional risk decision model considering the retailer's default risk. This paper studies how retailers and suppliers maximize their own interests by setting up order and pricing decisions, and draws the best factoring interest rate that the factoring firms should make.

Summary

By Theorem 1, theorem 3 and Theorem 5, it is known that when the retailer does not exist default, considering the risk aversion, the enterprise seeks the maximum profit, the bank has the optimal interest rate to satisfy the sufficient and necessary conditions. According to the optimal interest rate, the supplier can make the optimal wholesale price, and the retailer will get the optimal order quantity.

(5)

Under the condition of certain conditions, the optimal solution of the article model shows that the cooperation mode is feasible, and the three party can get the best goal. How to reduce the conditions to achieve this goal still needs a certain access mechanism, the prevention and control mechanism, and the need for legal protection. This paper only considers the CVaR model of supply chain finance under the account receivable factoring model, and the other two kinds of financing have not been taken into consideration, and therefore need further study.

Reference:

[1]Ma Shu-jian, Zhao Cheng-guo, Lu Ning. The Decision Analysis of CVaR Risk Control of the Three Parts in Supply Chain Finance Based on the advance payments financing mode[J].Journal of Mathematics in Practice and Theory, 2016 (24) :88-97.

[2]Y Sheffi, J.B. Rice. Supply chain management under the threat of international terrorism[J]. The International Journal of Logistics Management, 2003, 12(2):1-11.

[3]Holfmann E. supply chain finance: some conceptual insights [J]. Logistic Management- Innovative Logistic concepts, 2005(5):203-214.

[4]Yue-fei Hu.Financial background innovation and concept definition of supply chain [J].Journal of Financial Research, 2009, (8):194-206.

[5]Sopranzetti B J. The economics of factoring accounts receivable[J]. Journal of Economics & Business, 1998, 50(4): 339-359.

[6]Leora Klapper. The Role of Reverse Factoring in Supplier Financing of Small and Medium Sized Enterprises[J].World Bank, 2004; 3-24.

[7]Yu Hui, Ma Yun-lin. The supply chain finance model—based on the order-to-factoring mode [J].Systems Engineering—Theory & Practice.2015, 35(7):1733-1743.

[8]Zhou Yan-ju, Qiu Wan-hua, Wang Zong-run.Optimal Ordering Model for Multi-Products with CVaR Constraints [J].Chinese Journal of Management Science, 2006, 05:62-67.

[9]Zhu C B, Jian-Hua J I, Zeng S Q. Supply Chain Ordering Decision and Coordination Mechanism Based on CVa R under Supply Disruption[J]. Journal of Industrial Engineering & Engineering Management, 2015.

References

Related documents

Field experiments were conducted at Ebonyi State University Research Farm during 2009 and 2010 farming seasons to evaluate the effect of intercropping maize with

Study of the distribution of Malassezia species in patients with pityriasis versicolor and healthy individuals in Tehran, Iran. Distribution of Malassezia species

Based on these findings, I assume that the policy maker de- cides for the level of the firing restriction according to the wage of the average productivity group (p = 1) that would

12 Data Science Master Entrepreneur- ship Data Science Master Engineering entrepreneurship society engineering. Eindhoven University of Technology

The CreditCall CardEase Mobile application (www.cardeasemobile.com) enables merchants to use a smart phone or tablet together with a low cost card reader (from leading card

However, results generated from these stud- ies reveal a large list of non-overlapping differentially expressed genes; these discrepancies necessitate addi- tional studies to

To evaluate our implementation we compare it to the state-of-the-art Deep Learning object detector YOLO (Redmon and Farhadi, 2016) in both accuracy and speed.. 2