Marine transportation logistics alliance stability improving method based on block chain

Abstract

The invention provides a block chain-based marine transportation logistics alliance stability improvement method, which comprises the steps of S1, constructing a three-party evolutionary game model among members of a marine transportation logistics alliance based on a block chain platform; s2, defining members of the marine logistics alliance, and constructing a revenue function of the alliance members; s3, solving a balance point of the tripartite evolutionary game model by using the replicated dynamic equation, and analyzing a game evolutionary path; s4, analyzing stability strategies of alliance members under different influence conditions according to the balance point; and S5, establishing a sea transportation logistics alliance benefit distribution model based on a block chain platform by using the corrected Shapley value method. According to the method, an evolutionary game model between marine logistics alliance members is constructed based on a block chain platform to dynamically analyze the alliance stability, a benefit distribution model is established by using a modified Shapley value method, and the model is embedded into an intelligent contract. The method can assist the marine transportation logistics alliance to realize intellectualized and fair benefit distribution among members, and effectively improves the stability of the marine transportation logistics alliance.

Description

Technical Field

[0001] The present invention relates to the field of maritime logistics technology, and in particular to a method for improving the stability of a maritime logistics alliance based on blockchain. Background Art

[0002] More than 90% of the world's goods are transported by sea, and the improvement of the overall level of maritime logistics is crucial to the development of the global economy. In order to improve the efficiency and benefits of maritime logistics, maritime logistics companies, domestic logistics companies and foreign logistics companies have formed a logistics partnership for resource sharing, mutual benefit, complementary advantages and shared risks, namely the maritime logistics alliance.

[0003] At present, there are problems in the maritime logistics alliance, such as lack of trust among alliance entities, difficulty in information sharing, poor rationality and satisfaction of benefit distribution, cumbersome alliance work processes and difficulty in resource integration. The above problems lead to poor stability of the alliance. Summary of the invention

[0004] According to the technical problems raised above, a method for improving the stability of a maritime logistics alliance based on blockchain is provided. The present invention constructs an evolutionary game model among members of a maritime logistics alliance based on a blockchain platform to dynamically analyze the stability of the alliance, establishes a profit distribution model using a modified Shapely value method, and embeds the model into a smart contract. The invention can assist the maritime logistics alliance in realizing intelligent and fair profit distribution among members, and effectively improve the stability of the maritime logistics alliance.

[0005] The technical means adopted by the present invention are as follows:

[0006] A method for improving the stability of a maritime logistics alliance based on blockchain, comprising:

[0007] S1. Based on the blockchain platform, a three-party evolutionary game model among members of the maritime logistics alliance is constructed;

[0008] S2. Define the members of the maritime logistics alliance and construct the profit function of the alliance members;

[0009] S3. Use the replication dynamic equation to solve the equilibrium point of the three-party evolutionary game model and analyze the game evolution path;

[0010] S4. Analyze the stable strategies of alliance members under different influencing conditions based on the equilibrium point;

[0011] S5. Using the modified Shapely value method, a profit distribution model for the shipping logistics alliance is established based on the blockchain platform.

[0012] Furthermore, step S1 specifically includes:

[0013] S11. Set the model assumptions as follows:

[0014] Assume that the probability of a shipping logistics enterprise choosing to share information is x, and the probability of not sharing is 1-x; the probability of a foreign logistics enterprise choosing to share information is y, and the probability of not sharing is 1-y; the probability of a domestic logistics enterprise choosing to share information is z, and the probability of not sharing is 1-z, x, y, z∈[0,1];

[0015] Assume that the information sharing standard level is ω, λ i is the information conversion coefficient, is the total amount of information. If only two parties choose to share information, μ is the total amount of information.

[0016] Assume T i is the cost of operating the alliance members without forming an alliance model, π i is the normal income of alliance members, and the additional income from information sharing is A, β i is the shared income distribution coefficient of the alliance members; if only two parties share information, the shared income is M and the distribution coefficient is The economic loss caused by the party that does not share information being excluded by the sharing party is γ i ;

[0017] Assuming that the three parties share information, the cost of the alliance members caused by strategic and human factors is D i ;

[0018] Assume that the technical cost of signing a smart contract to achieve information sharing is C, C i technology costs for members;

[0019] S12. Based on the set model assumptions, the three-party evolutionary game benefits of maritime transport companies, overseas logistics companies, and domestic logistics companies under different circumstances are as follows:

[0020] Foreign logistics companies choose to share resources (y), and domestic logistics companies choose to share resources (z):

[0021] The maritime transport enterprise chooses to share resources (x): the benefits of the three parties are:

[0022] The maritime transport enterprise chooses not to share resources (1-x): the benefits of the three parties are: π1-γ1-T1, π2+ωλ2μ+Mθ2-C2, π3+ωλ3μ+Aθ3-C3;

[0023] Foreign logistics companies choose to share resources (y), while domestic logistics companies choose not to share resources (1-z):

[0024] The maritime transport enterprise chooses to share resources (x): the benefits of the three parties are: π1+ωλ1μ+Mθ1-C1, π2+ωλ2μ+Mθ2-C2, π3-γ3-T3;

[0025] The maritime transport enterprise chooses not to share resources (1-x): the benefits of the three parties are: π1-T1, π2-D2, π3-T3;

[0026] Foreign logistics companies choose not to share resources (1-y), and domestic logistics companies choose to share resources (z):

[0027] The maritime transport enterprise chooses to share resources (x): the benefits of the three parties are: π1+ωλ1μ+Mθ1-C1, π2-γ2-T, π3+ωλ3μ+Mθ3-C3;

[0028] The maritime transport enterprise chooses not to share resources (1-x): the benefits of the three parties are: π1-T, π2-T2, π3-D3;

[0029] Foreign logistics companies choose not to share resources (1-y), and domestic logistics companies choose not to share resources (1-z):

[0030] The maritime transport enterprise chooses to share resources (x): the benefits of the three parties are: π1-D1, π2-T2, π3-T3;

[0031] The maritime transport enterprise chooses not to share resources (1-x): the benefits of the three parties are: π1-T, π2-T2, π3-T3.

[0032] Further, step S2 specifically includes:

[0033] S21. Calculate the expected benefit U of information sharing for shipping logistics carriers l1 , the calculation formula is as follows:

[0034]

[0035] S22. Calculate the expected benefit U of the shipping logistics carrier if the information is not shared l2 , the calculation formula is as follows:

[0036] U l2 =yz(π1-γ1-T1)+y(1-z)(π1-T1)

[0037] +z(1-y)(π1-T1)+(1-y)(1-z)(π1-T1)

[0038] S23. Calculate the average expected revenue of the ocean logistics carrier The calculation formula is as follows:

[0039]

[0040] S24. Calculate the expected benefits of information sharing among overseas logistics enterprises U f1 , the calculation formula is as follows:

[0041]

[0042] S25. Calculate the expected benefits of information sharing among overseas logistics enterprises U f2 , the calculation formula is as follows:

[0043] U f2 =zx(π2-γ2-T2)+x(1-z)(π2-T2)

[0044] +z(1-x)(π2-T2)+(1-x)(1-z)(π2-T2)

[0045] S26. Calculate the average expected revenue of overseas logistics companies The calculation formula is as follows:

[0046]

[0047] S27. Calculate the expected benefits of information sharing among domestic logistics enterprises U c1 , the calculation formula is as follows:

[0048]

[0049] S28. Calculate the expected benefits U of domestic logistics enterprises without information sharing c2 , the calculation formula is as follows:

[0050] U c2 =xy(π3-γ3-T3)+x(1-y)(π3-T3)

[0051] +y(1-x)(π3-T3)+(1-x)(1-y)(π3-T3)

[0052] S29. Calculate the average expected revenue of domestic logistics enterprises The calculation formula is as follows:

[0053]

[0054] Further, step S3 specifically includes:

[0055] S31. Analyze the evolution path of maritime transport logistics enterprises:

[0056] S311. Establish a replication dynamic equation for the information sharing strategy of maritime transport logistics enterprises, as follows:

[0057]

[0058] S312. According to the stability theorem of the replication dynamic equation:

[0059] like Recorded as but Whatever proportion of standardized information sharing a maritime transport logistics company decides to conduct is a stable strategy that will not change over time;

[0060] like Let F(x) = 0, indicating that x = 0 and x = 1 are two equilibrium points;

[0061] when hour, is the stable point in the evolution path analysis, that is, the proportion of domestic logistics enterprises deciding to share standardized information is higher than When doing so, maritime transport and logistics companies will also choose to share information;

[0062] when hour, is the stable point in the evolution path analysis, that is, the proportion of domestic logistics enterprises choosing information sharing is lower than When doing so, due to cost constraints and other comprehensive considerations, maritime transport logistics companies may decide not to share standardized information;

[0063] S32. Analyze the evolution path of overseas logistics companies:

[0064] S321. Establish a replication dynamic equation for the information sharing strategy of maritime transport logistics enterprises, as follows:

[0065]

[0066] S322. According to the stability theorem of the replication dynamic equation:

[0067] like Recorded as but Whatever proportion of standardized information sharing an overseas logistics company decides to conduct is a stable strategy that will not change over time;

[0068] like Let F(y) = 0, indicating that y = 0 and y = 1 are two equilibrium points;

[0069] when hour, is the stable point in the evolution path analysis, that is, the proportion of domestic logistics enterprises deciding to share standardized information is higher than When foreign logistics companies decide to share standardized information;

[0070] when hour, is the stable point in the evolution path analysis, that is, the proportion of domestic logistics enterprises choosing information sharing is lower than When foreign logistics companies decide not to share standardized information;

[0071] S33. Analysis of the evolution path of domestic logistics enterprises:

[0072] S331. Establish the replication dynamic equation of the information sharing strategy of the maritime transport logistics enterprise as follows:

[0073]

[0074] S332. According to the stability theorem of the replication dynamic equation:

[0075] like Recorded as but Domestic logistics enterprises have a stable strategy regardless of the proportion of information sharing they choose;

[0076] like Let F(z) = 0, indicating that z = 0 and z = 1 are two equilibrium points;

[0077] when hour, is the stable point in the evolution path analysis, that is, the proportion of overseas logistics enterprises choosing information sharing is higher than When domestic logistics companies decide to share standardized information;

[0078] when hour, As the stable point in the evolution path analysis, the proportion of information sharing selected by overseas logistics enterprises is lower than At that time, domestic logistics companies decided not to share standardized information in order to avoid losses.

[0079] Further, step S4 specifically includes:

[0080] S41. According to the replication dynamic equation in step S3, the Jacobian matrix of the tripartite replication dynamic system is derived as follows:

[0081]

[0082]

[0083] S42. Let F(x)=F(y)=F(z)=0, and the local equilibrium points are E1(0,0,0), E2(0,0,1), E3(0,1,0), E4(0,1,1), E5(1,0,0), E6(1,0,1), E7(1,1,0), E8(1,1,1). If the eigenvalue of the Jacobi matrix is ​​negative, the local equilibrium point is an evolutionary stable strategy.

[0084] S43. The application of blockchain platform makes the benefits of information sharing of alliance members greater than the benefits of not sharing.

[0085] S44. Based on step S43, two assumptions are proposed as follows:

[0086] Hypothesis 1: When only two parties choose to share, the overall benefits of the alliance are greater than the benefits of not sharing, that is:

[0087]

[0088] Assumption 2: When only one party chooses to share, the normal income of the members is higher than the income of the alliance chain, that is: (π i +ωλ i μ+Mθ i -C i )<π i -T i ;

[0089] S45. Based on the assumptions in step S44, the local stability analysis results of the three-party evolutionary game of the alliance are obtained. From the perspective of maximizing the interests of the alliance members, E8 (1,1,1) is a strategy that is beneficial to all three game entities, that is, all alliance members choose the information sharing strategy.

[0090] Furthermore, step S5 specifically includes:

[0091] S51. Considering logistics risk, input resource value, information contribution and logistics stability, a modified Shapley value model is established as follows:

[0092] Φ i '=Φ i +v(τ)(ω i -1 / n)

[0093] Φ'=(Φ1',Φ2',...,Φ n ')

[0094]

[0095] Where v(τ) is the total revenue of the entire shipping logistics alliance, Φ represents the original benefit obtained under the standard Shapley value model; Φ'=(Φ1',Φ2',...,Φ n ') represents the benefit distribution of the modified Shapley value method; ω i is the comprehensive benefit distribution influencing factor of the i-th alliance member, representing the sum of the four factors modified according to a certain weight; f j , j = 1, 2, 3, 4 are the weights of the above-mentioned 4 modified benefit distribution influencing factors. The weight coefficients of the influencing factors are obtained by consulting managers in the shipping logistics industry and related experts using the hierarchical analysis method;

[0096] S52, determine the correction factor parameters:

[0097] S521. Determine the value of input resources:

[0098] Assume that the maritime logistics alliance has n members and invests m resources in total. P represents the value of resources invested by members. Assume that the correction coefficient of the value of invested resources is C, and K represents the resource value impact coefficient. The value of K depends on the role of the resource in the alliance. K<0 indicates that the investment of the resource has a negative effect on the output of the alliance's interests.

[0099] Calculate the input resource market value matrix as follows:

[0100]

[0101] Calculate the input resource market value correction coefficient matrix as follows:

[0102]

[0103] Calculate the input resource value matrix as follows:

[0104]

[0105] Let E = [1 1...1] 1n , then calculate the impact factor θ of the benefit distribution of member i's input resource value i ,as follows:

[0106]

[0107] S522. Determine risk factors:

[0108] Assume that the total number of members of the maritime logistics alliance is n, ΔR represents the value of logistics risk factors, r represents the risk factor benefit distribution influencing factor; R i '1' indicates the risk capability of members after joining the alliance, R i '1 represents the risk capacity of members before joining the alliance; Ri '2' indicates the risk capacity of the alliance after the member joins, R i '2 represents the risk capacity of the alliance before joining the member;

[0109] Calculate the change value ΔR of alliance members’ risk factors i ,as follows:

[0110] ΔR i =ΔR i1 -ΔR i2

[0111] Among them, ΔR i1 =R i '1'-R i '1, ΔR i2 =R i '2'-R i '2;

[0112] Calculate the risk factor benefit distribution impact factor r of member i i ,as follows:

[0113]

[0114] S523. Determine logistics:

[0115] Assume that the total number of members of the maritime logistics alliance is n, ΔS represents the logistics stability measurement value, S represents the influencing factor of logistics stability benefit distribution; S i '1' indicates the logistics stability level of the member after joining the alliance, S i '1 represents the logistics stability level of the members before joining the alliance. i '2' indicates the logistics stability level of the alliance after joining the member, S i '2 represents the logistics stability level of the alliance before joining the member;

[0116] Calculate the change measurement value ΔS of the logistics stability factor of alliance members as follows:

[0117]

[0118] in,

[0119] Calculate the impact factor S of the logistics stability factor benefit distribution of member i i ,as follows:

[0120]

[0121] S524. Determine the information contribution of alliance members:

[0122] Assume that information contribution is U, and the information contribution of logistics members is related to the data verification service A, shared information B, and maintenance node C provided by logistics members. According to the calculation of information contribution by blockchain technology and the advice of experts, the weights of providing data verification service A, sharing information B, and maintaining node C are set at 0.4, 0.3, and 0.3 respectively.

[0123] Calculate the information contribution U for new alliance members i1 ,as follows:

[0124] U i1 =A i1 ×0.4+B i1 ×0.3+C i1 ×0.3

[0125] Calculate the information contribution U of the alliance after the new member joins i2 ,as follows:

[0126] U i2 =A i2 ×0.4+B i2 ×0.3+C i2 ×0.3

[0127] Calculate the alliance member information contribution change measurement value ΔU as follows:

[0128] ΔU=U i1 -U i2 =0.4(A i1 -A i2 )+0.3(B i1 -B i2 )+0.3(C i1 -C i2 )

[0129] Calculate member i's information contribution and benefit distribution impact factor u i ,as follows:

[0130]

[0131] The modified Shapley value method can not only reflect the role played by alliance members in the maritime logistics transportation process, but also obtain the best distribution plan for alliance benefits.

[0132] Compared with the prior art, the present invention has the following advantages:

[0133] 1. The present invention provides a method for improving the stability of a shipping logistics alliance based on blockchain. An evolutionary game model among members of the shipping logistics alliance is constructed based on the blockchain platform to dynamically analyze the stability of the alliance, obtain the game evolution stability points under different situations and the optimal selection strategies of alliance members, and use numerical simulation to verify that reasonable benefit distribution is the most important factor affecting the stability of the alliance.

[0134] 2. The present invention provides a method for improving the stability of a shipping logistics alliance based on blockchain. Based on the blockchain platform, a revised profit distribution model is constructed using the Shapely value method, and a profit distribution smart contract is designed and implemented, thereby realizing profit distribution in an intelligent and fair manner.

[0135] Based on the above reasons, the present invention can be widely promoted in the fields of marine logistics and the like. BRIEF DESCRIPTION OF THE DRAWINGS

[0136] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0137] Figure 1 The figure is a flow chart of the method of the present invention.

[0138] Figure 2 A standard horizontal three-dimensional trajectory diagram for information sharing provided by an embodiment of the present invention.

[0139] Figure 3 A standard horizontal two-dimensional trajectory diagram for information sharing provided by an embodiment of the present invention.

[0140] Figure 4 A three-dimensional trajectory diagram of information sharing risk costs provided by an embodiment of the present invention.

[0141] Figure 5 A two-dimensional trajectory diagram of information sharing risk cost provided by an embodiment of the present invention.

[0142] Figure 6 A three-dimensional trajectory diagram of the technology investment cost provided in an embodiment of the present invention.

[0143] Figure 7 A two-dimensional trajectory diagram of the technology investment cost provided in an embodiment of the present invention.

[0144] Figure 8 A three-dimensional trajectory diagram of reasonable benefit distribution provided by an embodiment of the present invention.

[0145] Fig. 9A two-dimensional trajectory diagram of reasonable benefit distribution provided by an embodiment of the present invention.

[0146] Fig.10 This is the compilation result of the profit distribution smart contract provided in the embodiment of the present invention.

[0147] Fig.11 This is the compilation result of the profit distribution smart contract provided in the embodiment of the present invention.

[0148] Fig.12 The benefit distribution smart contract deployment result provided in the embodiment of the present invention.

[0149] Fig.13 The benefit distribution smart contract deployment result provided in the embodiment of the present invention.

[0150] Fig.14 The benefit distribution smart contract deployment result provided in the embodiment of the present invention.

[0151] Fig.15 The benefit distribution smart contract deployment result provided in the embodiment of the present invention. DETAILED DESCRIPTION

[0152] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0153] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0154] like Figure 1 As shown, the present invention provides a method for improving the stability of a maritime logistics alliance based on blockchain, comprising:

[0155] S1. Based on the blockchain platform, a three-party evolutionary game model among members of the maritime logistics alliance is constructed;

[0156] S2. Define the members of the maritime logistics alliance and construct the profit function of the alliance members;

[0157] S3. Use the replication dynamic equation to solve the equilibrium point of the three-party evolutionary game model and analyze the game evolution path;

[0158] S4. Analyze the stable strategies of alliance members under different influencing conditions based on the equilibrium point;

[0159] S5. Using the modified Shapely value method, a profit distribution model for the shipping logistics alliance is established based on the blockchain platform.

[0160] In specific implementation, as a preferred embodiment of the present invention, step S1 specifically includes:

[0161] S11. Set the model assumptions as follows:

[0162] Assume that the probability of a shipping logistics enterprise choosing to share information is x, and the probability of not sharing is 1-x; the probability of a foreign logistics enterprise choosing to share information is y, and the probability of not sharing is 1-y; the probability of a domestic logistics enterprise choosing to share information is z, and the probability of not sharing is 1-z, x, y, z∈[0,1];

[0163] Assume that the information sharing standard level is ω, λ i is the information conversion coefficient, is the total amount of information. If only two parties choose to share information, μ is the total amount of information.

[0164] Assume T i is the cost of operating the alliance members without forming an alliance model, π i is the normal income of alliance members, and the additional income from information sharing is A, β i is the shared income distribution coefficient of the alliance members; if only two parties share information, the shared income is M and the distribution coefficient is The economic loss caused by the party that does not share information being excluded by the sharing party is γ i ;

[0165] Assuming that the three parties share information, the cost of the alliance members caused by strategic and human factors is D i ;

[0166] Assume that the technical cost of signing a smart contract to achieve information sharing is C, C i technology costs for members;

[0167] S12. Based on the set model assumptions, the three-party evolutionary game benefits of maritime transport companies, overseas logistics companies, and domestic logistics companies under different circumstances are as follows:

[0168] Foreign logistics companies choose to share resources (y), and domestic logistics companies choose to share resources (z):

[0169] The maritime transport enterprise chooses to share resources (x): the benefits of the three parties are

[0170] The maritime transport enterprise chooses not to share resources (1-x): the benefits of the three parties are: π1-γ1-T1, π2+ωλ2μ+Mθ2-C2, π3+ωλ3μ+Aθ3-C3;

[0171] Foreign logistics companies choose to share resources (y), while domestic logistics companies choose not to share resources (1-z):

[0172] The maritime transport enterprise chooses to share resources (x): the benefits of the three parties are: π1+ωλ1μ+Mθ1-C1, π2+ωλ2μ+Mθ2-C2, π3-γ3-T3;

[0173] The maritime transport enterprise chooses not to share resources (1-x): the benefits of the three parties are: π1-T1, π2-D2, π3-T3;

[0174] Foreign logistics companies choose not to share resources (1-y), and domestic logistics companies choose to share resources (z):

[0175] The maritime transport enterprise chooses to share resources (x): the benefits of the three parties are: π1+ωλ1μ+Mθ1-C1, π2-γ2-T, π3+ωλ3μ+Mθ3-C3;

[0176] The maritime transport enterprise chooses not to share resources (1-x): the benefits of the three parties are: π1-T, π2-T2, π3-D3;

[0177] Foreign logistics companies choose not to share resources (1-y), and domestic logistics companies choose not to share resources (1-z):

[0178] The maritime transport enterprise chooses to share resources (x): the benefits of the three parties are: π1-D1, π2-T2, π3-T3;

[0179] The maritime transport enterprise chooses not to share resources (1-x): the benefits of the three parties are: π1-T, π2-T2, π3-T3.

[0180] In specific implementation, as a preferred embodiment of the present invention, step S2 specifically includes:

[0181] S21. Calculate the expected benefit U of information sharing for shipping logistics carriers l1 , the calculation formula is as follows:

[0182]

[0183] S22. Calculate the expected benefit U of the shipping logistics carrier if the information is not shared l2 , the calculation formula is as follows:

[0184] U l2 =yz(π1-γ1-T1)+y(1-z)(π1-T1)

[0185] +z(1-y)(π1-T1)+(1-y)(1-z)(π1-T1)

[0186] S23. Calculate the average expected revenue of the ocean logistics carrier The calculation formula is as follows:

[0187]

[0188] S24. Calculate the expected benefits of information sharing among overseas logistics enterprises U f1 , the calculation formula is as follows:

[0189]

[0190] S25. Calculate the expected benefits of information sharing among overseas logistics enterprises U f2 , the calculation formula is as follows:

[0191] U f2 =zx(π2-γ2-T2)+x(1-z)(π2-T2)

[0192] +z(1-x)(π2-T2)+(1-x)(1-z)(π2-T2)

[0193] S26. Calculate the average expected revenue of overseas logistics companies The calculation formula is as follows:

[0194]

[0195] S27. Calculate the expected benefits of information sharing among domestic logistics enterprises U c1 , the calculation formula is as follows:

[0196]

[0197] S28. Calculate the expected benefits U of domestic logistics enterprises without information sharing c2 , the calculation formula is as follows:

[0198] U c2 =xy(π3-γ3-T3)+x(1-y)(π3-T3)

[0199] +y(1-x)(π3-T3)+(1-x)(1-y)(π3-T3)

[0200] S29. Calculate the average expected revenue of domestic logistics enterprises The calculation formula is as follows:

[0201]

[0202] In specific implementation, as a preferred embodiment of the present invention, step S3 specifically includes:

[0203] S31. Analyze the evolution path of maritime transport logistics enterprises:

[0204] S311. Establish a replication dynamic equation for the information sharing strategy of maritime transport logistics enterprises, as follows:

[0205]

[0206] S312. According to the stability theorem of the replication dynamic equation:

[0207] like Recorded as but Whatever proportion of standardized information sharing a maritime transport logistics company decides to conduct is a stable strategy that will not change over time;

[0208] like Let F(x) = 0, indicating that x = 0 and x = 1 are two equilibrium points;

[0209] when hour, is the stable point in the evolution path analysis, that is, the proportion of domestic logistics enterprises deciding to share standardized information is higher than When doing so, maritime transport and logistics companies will also choose to share information;

[0210] when hour, is the stable point in the evolution path analysis, that is, the proportion of domestic logistics enterprises choosing information sharing is lower than When doing so, due to cost constraints and other comprehensive considerations, maritime transport logistics companies may decide not to share standardized information;

[0211] S32. Analyze the evolution path of overseas logistics companies:

[0212] S321. Establish a replication dynamic equation for the information sharing strategy of maritime transport logistics enterprises, as follows:

[0213]

[0214] S322. According to the stability theorem of the replication dynamic equation:

[0215] like Recorded as but Whatever proportion of standardized information sharing an overseas logistics company decides to conduct is a stable strategy that will not change over time;

[0216] like Let F(y) = 0, indicating that y = 0 and y = 1 are two equilibrium points;

[0217] when hour, is the stable point in the evolution path analysis, that is, the proportion of domestic logistics enterprises deciding to share standardized information is higher than When foreign logistics companies decide to share standardized information;

[0218] when hour, is the stable point in the evolution path analysis, that is, the proportion of domestic logistics enterprises choosing information sharing is lower than When foreign logistics companies decide not to share standardized information;

[0219] S33. Analysis of the evolution path of domestic logistics enterprises:

[0220] S331. Establish the replication dynamic equation of the information sharing strategy of the maritime transport logistics enterprise as follows:

[0221]

[0222] S332. According to the stability theorem of the replication dynamic equation:

[0223] like but Domestic logistics enterprises have a stable strategy regardless of the proportion of information sharing they choose;

[0224] like Let F(z) = 0, indicating that z = 0 and z = 1 are two equilibrium points;

[0225] when hour, is the stable point in the evolution path analysis, that is, the proportion of overseas logistics enterprises choosing information sharing is higher than When domestic logistics companies decide to share standardized information;

[0226] when hour, As the stable point in the evolution path analysis, the proportion of information sharing selected by overseas logistics enterprises is lower than At that time, domestic logistics companies decided not to share standardized information in order to avoid losses.

[0227] In specific implementation, as a preferred embodiment of the present invention, step S4 specifically includes:

[0228] S41. According to the replication dynamic equation in step S3, the Jacobian matrix of the tripartite replication dynamic system is derived as follows:

[0229]

[0230] S42. Let F(x)=F(y)=F(z)=0, and the local equilibrium points are E1(0,0,0), E2(0,0,1), E3(0,1,0), E4(0,1,1), E5(1,0,0), E6(1,0,1), E7(1,1,0), E8(1,1,1). If the eigenvalue of the Jacobi matrix is ​​negative, the local equilibrium point is an evolutionarily stable strategy. The Jacobi eigenvalues ​​corresponding to the equilibrium points are shown in Table 1.

[0231] Table 1 Eigenvalues ​​of the Jacobi matrix corresponding to the equilibrium point

[0232]

[0233] S43. The application of blockchain platform makes the benefits of information sharing of alliance members greater than the benefits of not sharing.

[0234] S44. Based on step S43, two assumptions are proposed as follows:

[0235] Hypothesis 1: When only two parties choose to share, the overall benefits of the alliance are greater than the benefits of not sharing, that is:

[0236]

[0237] Assumption 2: When only one party chooses to share, the normal income of the members is higher than the income of the alliance chain, that is: (π i +ωλ i μ+Mθ i -C i )<π i -T i ;

[0238] S45. Based on the assumptions in step S44, the local stability analysis results of the three-party evolutionary game of the alliance are obtained. From the perspective of maximizing the interests of the alliance members, E8 (1,1,1) is a strategy that is beneficial to all three game entities, that is, all alliance members choose the information sharing strategy. The local stability analysis results of the three-party evolutionary game of the alliance are shown in Table 2.

[0239] Table 2 Equilibrium point and stability

[0240]

[0241] In specific implementation, as a preferred embodiment of the present invention, step S5 specifically includes:

[0242] S51. Considering logistics risk, input resource value, information contribution and logistics stability, a modified Shapley value model is established as follows:

[0243] Φ i '=Φ i +v(τ)(ω i -1 / n)

[0244] Φ'=(Φ1',Φ2',...,Φ n ')

[0245]

[0246] Where v(τ) is the total revenue of the entire shipping logistics alliance, Φ represents the original benefit obtained under the standard Shapley value model; Φ'=(Φ1',Φ2',...,Φ n ') represents the benefit distribution of the modified Shapley value method; ω i is the comprehensive benefit distribution influencing factor of the i-th alliance member, representing the sum of the four factors modified according to a certain weight; f j , j = 1, 2, 3, 4 are the weights of the four modified benefit distribution influencing factors mentioned above. By consulting managers engaged in the shipping logistics industry and related experts, the weight coefficients of the influencing factors were obtained using the hierarchical analysis method, as shown in Table 3.

[0247] Table 3 Weight coefficients

[0248] S52, determine the correction factor parameters:

[0249] S521. Determine the value of input resources:

[0250] Assume that the maritime logistics alliance has n members and invests m resources in total. P represents the value of resources invested by members. Assume that the correction coefficient of the value of invested resources is C, and K represents the resource value impact coefficient. The value of K depends on the role of the resource in the alliance. K<0 indicates that the investment of the resource has a negative effect on the output of the alliance's interests.

[0251] Calculate the input resource market value matrix as follows:

[0252]

[0253] Calculate the input resource market value correction coefficient matrix as follows:

[0254]

[0255] Calculate the input resource value matrix as follows:

[0256]

[0257] Let E = [1 1...1] 1n , then calculate the impact factor θ of the benefit distribution of member i's input resource value i ,as follows:

[0258]

[0259] S522. Determine risk factors:

[0260] Assume that the total number of members of the maritime logistics alliance is n, ΔR represents the value of logistics risk factors, r represents the risk factor benefit distribution influencing factor; R i '1' indicates the risk capability of members after joining the alliance, R i '1 represents the risk capacity of members before joining the alliance; R i '2' indicates the risk capacity of the alliance after the member joins, R i '2 represents the risk capacity of the alliance before joining the member;

[0261] Calculate the change value ΔR of alliance members’ risk factors i ,as follows:

[0262] ΔR i =ΔR i1 -ΔR i2

[0263] Among them, ΔR i1 =R i '1'-R i '1, ΔR i2 =R i '2'-R i '2;

[0264] Calculate the risk factor benefit distribution impact factor r of member i i ,as follows:

[0265]

[0266] S523. Determine logistics:

[0267] Assume that the total number of members of the maritime logistics alliance is n, ΔS represents the logistics stability measurement value, S represents the influencing factor of logistics stability benefit distribution; S i '1' indicates the logistics stability level of the member after joining the alliance, S i '1 represents the logistics stability level of the members before joining the alliance. i '2' indicates the logistics stability level of the alliance after joining the member, S i '2 represents the logistics stability level of the alliance before joining the member;

[0268] Calculate the change measurement value ΔS of the logistics stability factor of alliance members as follows:

[0269]

[0270] in,

[0271] Calculate the impact factor S of the logistics stability factor benefit distribution of member i i ,as follows:

[0272]

[0273] S524. Determine the information contribution of alliance members:

[0274] Assume that information contribution is U, and the information contribution of logistics members is related to the data verification service A, shared information B, and maintenance node C provided by logistics members. According to the calculation of information contribution by blockchain technology and the advice of experts, the weights of providing data verification service A, sharing information B, and maintaining node C are set at 0.4, 0.3, and 0.3 respectively.

[0275] Calculate the information contribution U for new alliance members i1 ,as follows:

[0276] U i1 =A i1 ×0.4+B i1 ×0.3+C i1 ×0.3

[0277] Calculate the information contribution U of the alliance after the new member joins i2 ,as follows:

[0278] U i2 =Ai2 ×0.4+B i2 ×0.3+C i2 ×0.3

[0279] Calculate the alliance member information contribution change measurement value ΔU as follows:

[0280] ΔU=U i1 -U i2 =0.4(A i1 -A i2 )+0.3(B i1 -B i2 )+0.3(C i1 -C i2 )

[0281] Calculate member i's information contribution and benefit distribution impact factor u i ,as follows:

[0282]

[0283] The modified Shapley value method can not only reflect the role played by alliance members in the maritime logistics transportation process, but also obtain the best distribution plan for alliance benefits.

[0284] Example

[0285] In this embodiment, in order to test the validity of the evolutionary analysis results and the feasibility of the benefit distribution model, the present invention uses MATLAB to implement numerical simulation and uses Solidity language to implement smart contract writing in the Remix environment. This experiment was run on a computer with an Intel(R) Core(TM) i5-1035G1 CPU@1.00GHz 1.19GHz processor and 8GB of memory. The experimental contents of the present invention are as follows:

[0286] 1. Simulation analysis

[0287] Parameter Assignment

[0288] Based on the survey of personnel in the maritime logistics industry and the suggestions of simulation experts, the conditions that the initial parameters should meet are summarized as follows:

[0289] (1) ω represents the level of information sharing standards. If the information sharing standards of the three parties can be unified, then ω = 1; otherwise, ω = 0; if the information standards are partially consistent, then ω∈(0, 1).

[0290] (2)λ irepresents the information conversion coefficient, λ1, λ2, and λ3 represent the information conversion coefficients of shipping logistics companies, foreign logistics companies, and domestic logistics companies respectively. The information conversion coefficient of domestic logistics companies is higher than that of foreign logistics companies; at the same time, the information conversion coefficient of foreign logistics companies is higher than that of shipping logistics companies, so λ3>λ2>λ1.

[0291] (3)β i represents the information sharing benefit allocation coefficient, β1, β2, and β3 represent the benefit allocation coefficients of shipping logistics companies, overseas logistics companies, and domestic logistics companies, respectively. Domestic logistics companies, as the leading companies, contribute the most to the overall business, so β3>β2 and β3>β1.

[0292] (4) A represents the additional benefits obtained from information sharing, and M represents the benefits obtained when only two parties choose to share information. The additional benefits obtained when the three parties choose to share information on the chain are higher than the additional benefits obtained when any two parties choose to share information on the chain, that is, A>M.

[0293] (5)C i represents the technical cost, γ i Indicates economic loss, D i represents the risk cost of information sharing, π represents the normal return of non-information sharing, and the corresponding subscripts 1-3 represent the parameters corresponding to shipping logistics enterprises, foreign logistics enterprises, and domestic logistics enterprises. As the leading enterprise, the domestic logistics enterprise has higher information sharing technology costs and higher economic losses caused by non-information sharing than the other two members; the normal return of shipping logistics enterprises is higher than that of domestic and foreign logistics enterprises, so C3>C2 and C3>C1, γ3>γ2 and γ3>γ1, D3>D2 and D3>D1, π1>π2 and π1>π3.

[0294] According to the above conditions, the initial willingness values ​​of the three-party game entities are set to x=y=z=0.5, ω=0.5, λ1=0.2, λ2=0.3, λ3=0.5, A=10, β1=β2=0.3, β3=0.4, π1=7, π2=π3=5, θ i =0.5, M=6, γ1=γ2=2.5, γ3=3.5, C1=C2=2.8, C3=4, μ=25, D1=D2=2.1, D3=3.3.

[0295] Numerical simulation

[0296] Three-dimensional simulation and two-dimensional simulation were performed on the four factors of information sharing standard level, information sharing risk cost, information sharing technology investment cost and reasonable benefit distribution. The three-dimensional simulation represents the decision changes of alliance members, and the two-dimensional simulation represents the critical change value of each factor.

[0297] (1) The impact of information sharing standards on alliance stability

[0298] like Figure 2 , 3 As shown in the figure, the simulation of the impact of information sharing among the three parties when the information sharing standard level takes different values. The critical value of the information sharing standard level ω is 0.46-0.47. When ω is lower than the critical value, the equilibrium point tends to (0,0,0); when ω is higher than the critical value, x, y and z all converge to 1, and z converges to 1 faster than y and x. The results show that the level of information sharing standards will affect the choice of information sharing strategies of alliance members. When ω>0.46, the three parties will choose information sharing. The higher the level of information sharing standards, the stronger the willingness of alliance members to share information.

[0299] (2) The impact of information sharing risk costs on alliance stability

[0300] like Figure 4 , 5 As shown in the figure, it is a simulation of the impact of information sharing among the three parties when the information sharing risk cost takes different values. The critical value of D3 is 3.9-4.0. When D3 is lower than the critical value, x converges to 1; otherwise, x converges to 0. The critical values ​​of D1 and D2 are 2.05-2.1. When D1 and D2 are lower than the critical value, y and z converge to 1; otherwise, y and z converge to 0, and z converges to 0 faster than y, indicating that overseas logistics companies are more sensitive to information sharing risks. When D i When it is higher than the critical value, x, y and z converge to 0; otherwise, x, y and z converge to 1. The results show that as the risk of information sharing increases, the willingness of alliance members to share information decreases.

[0301] (3) The impact of technology investment costs on alliance stability

[0302] like Figure 6 , 7 As shown in the figure, it is a simulation of the impact of information sharing among the three parties when the input cost of information sharing technology takes different values. The critical value of C3 is 4-4.1. When C3 is lower than the critical value, z converges to 1. The smaller C3 is, the faster z converges to 1; when C3 is higher than the critical value, z converges to 0. The larger C3 is, the faster z converges to 0. The critical values ​​of C2 and C1 are 2.8-2.85. When C2 and C1 are lower than the critical value, y and x converge to 1; otherwise, y and x converge to 0, and x converges to 0 faster than y, indicating that domestic logistics enterprises are more sensitive to the input cost of information sharing. The results show that when the cost of information sharing exceeds the expectations of enterprises, alliance members will give up information sharing.

[0303] (4) Impact of technology investment costs on alliance stability

[0304] like Figure 8, 9 As shown in Figure 1, the simulation of the impact of information sharing among the three parties when the information sharing benefit distribution coefficient takes different values. When the information sharing benefit distribution is extremely unreasonable, z first shows a trend of rapidly converging to 1, but is eventually forced to decrease due to the rapid convergence of y and x to 0, and the equilibrium point tends to (0,0,0). The results show that average benefit distribution can better promote alliance members to choose information sharing strategies.

[0305] 2. Smart Contract Design

[0306] According to the business logic of the maritime logistics alliance's profit distribution, variables need to be declared and can be called in related function functions. Due to the particularity of smart contracts, their variables are different from those of other development languages. In addition to state variables, smart contracts also involve special variables, as shown in Table 4-5.

[0307] Table 4 State variables

[0308]

[0309] Table 5 Special variables

[0310]

[0311] The time functions involved in the embodiment of the present invention are shown in Table 6.

[0312] Table 6 Event functions

[0313]

[0314]

[0315] The functional functions used in the embodiment of the present invention are shown in Table 7.

[0316] Table 7 Function

[0317]

[0318] In the present invention, the input of the smart contract is the modified impact factor parameter, and the output is the benefits obtained by each member of the alliance. The contract can automatically execute the benefit distribution model and record the results on the blockchain to ensure the transparency and fairness of the benefit distribution. The specific results are as follows Figure 10-15 shown.

[0319] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for improving the stability of a maritime logistics alliance based on blockchain, characterized in that: include: S1. Based on the blockchain platform, a three-party evolutionary game model among members of the maritime logistics alliance is constructed; S2. Define the members of the maritime logistics alliance and construct the profit function of the alliance members; S3. Use the replication dynamic equation to solve the equilibrium point of the three-party evolutionary game model and analyze the game evolution path; S4. Analyze the stable strategies of alliance members under different influencing conditions based on the equilibrium point; S5. Using the modified Shapely value method, a profit distribution model for the shipping logistics alliance is established based on the blockchain platform.

2. According to the method for improving the stability of the maritime logistics alliance based on blockchain in claim 1, it is characterized in that: Step S1 specifically includes: S11. Set the model assumptions as follows: Assume that the probability of a shipping logistics enterprise choosing to share information is x, and the probability of not sharing is 1-x; the probability of a foreign logistics enterprise choosing to share information is y, and the probability of not sharing is 1-y; the probability of a domestic logistics enterprise choosing to share information is z, and the probability of not sharing is 1-z, x, y, z∈[0,1]; Assume that the information sharing standard level is ω, λ i is the information conversion coefficient, is the total amount of information. If only two parties choose to share information, μ is the total amount of information. Assume T i is the cost of operating the alliance members without forming an alliance model, π i is the normal income of alliance members, and the additional income from information sharing is A, β i is the shared income distribution coefficient of the alliance members; if only two parties share information, the shared income is M and the distribution coefficient is The economic loss caused by the party that does not share information being excluded by the sharing party is γ i ; Assuming that the three parties share information, the cost of the alliance members caused by strategic and human factors is D i ; Assume that the technical cost of signing a smart contract to achieve information sharing is C, C i technology costs for members; S12. Based on the set model assumptions, the three-party evolutionary game benefits of maritime transport companies, overseas logistics companies, and domestic logistics companies under different circumstances are as follows: Foreign logistics companies choose to share resources (y), and domestic logistics companies choose to share resources (z): The maritime transport enterprise chooses to share resources (x): the benefits of the three parties are: The maritime transport enterprise chooses not to share resources (1-x): the benefits of the three parties are: π1-γ1-T1, π2+ωλ2μ+Mθ2-C2, π3+ωλ3μ+Aθ3-C3; Foreign logistics companies choose to share resources (y), while domestic logistics companies choose not to share resources (1-z): The maritime transport enterprise chooses to share resources (x): the benefits of the three parties are: π1+ωλ1μ+Mθ1-C1, π2+ωλ2μ+Mθ2-C2, π3-γ3-T3; The maritime transport enterprise chooses not to share resources (1-x): the benefits of the three parties are: π1-T1, π2-D2, π3-T3; Foreign logistics companies choose not to share resources (1-y), and domestic logistics companies choose to share resources (z): The maritime transport enterprise chooses to share resources (x): the benefits of the three parties are: π1+ωλ1μ+Mθ1-C1, π2-γ2-T, π3+ωλ3μ+Mθ3-C3; The maritime transport enterprise chooses not to share resources (1-x): the benefits of the three parties are: π1-T, π2-T2, π3-D3; Foreign logistics companies choose not to share resources (1-y), and domestic logistics companies choose not to share resources (1-z): The maritime transport enterprise chooses to share resources (x): the benefits of the three parties are: π1-D1, π2-T2, π3-T3; The maritime transport enterprise chooses not to share resources (1-x): the benefits of the three parties are: π1-T, π2-T2, π3-T3.

3. According to a method for improving the stability of a maritime logistics alliance based on blockchain according to claim 1, it is characterized in that: Step S2 specifically includes: S21. Calculate the expected benefit U of information sharing for shipping logistics carriers l1 , the calculation formula is as follows: S22. Calculate the expected benefit U of the shipping logistics carrier if the information is not shared l2 , the calculation formula is as follows: U l2 =yz(π1-γ1-T1)+y(1-z)(π1-T1) +z(1-y)(π1-T1)+(1-y)(1-z)(π1-T1) S23. Calculate the average expected revenue of the ocean logistics carrier The calculation formula is as follows: S24. Calculate the expected benefits of information sharing among overseas logistics enterprises U f1 , the calculation formula is as follows: S25. Calculate the expected benefits of information sharing among overseas logistics enterprises U f2 , the calculation formula is as follows: U f2 =zx(π2-γ2-T2)+x(1-z)(π2-T2) +z(1-x)(π2-T2)+(1-x)(1-z)(π2-T2) S26. Calculate the average expected revenue of overseas logistics companies The calculation formula is as follows: S27. Calculate the expected benefits of information sharing among domestic logistics enterprises U c1 , the calculation formula is as follows: S28. Calculate the expected benefits U of domestic logistics enterprises without information sharing c2 , the calculation formula is as follows: U c2 =xy(π3-γ3-T3)+x(1-y)(π3-T3) +y(1-x)(π3-T3)+(1-x)(1-y)(π3-T3) S29. Calculate the average expected revenue of domestic logistics enterprises The calculation formula is as follows:

4. A method for improving the stability of a maritime logistics alliance based on blockchain according to claim 1, characterized in that: Step S3 specifically includes: S31. Analyze the evolution path of maritime transport logistics enterprises: S311. Establish a replication dynamic equation for the information sharing strategy of maritime transport logistics enterprises, as follows: S312. According to the stability theorem of the replication dynamic equation: like Recorded as but Whatever proportion of standardized information sharing a maritime transport logistics company decides to conduct is a stable strategy that will not change over time; like Let F(x) = 0, indicating that x = 0 and x = 1 are two equilibrium points; when hour, is the stable point in the evolution path analysis, that is, the proportion of domestic logistics enterprises that decide to share standardized information is higher than When doing so, maritime transport and logistics companies will also choose to share information; when hour, is the stable point in the evolution path analysis, that is, the proportion of domestic logistics enterprises choosing information sharing is lower than When doing so, due to cost constraints and other comprehensive considerations, maritime transport logistics companies may decide not to share standardized information; S32. Analyze the evolution path of overseas logistics companies: S321. Establish a replication dynamic equation for the information sharing strategy of maritime transport logistics enterprises, as follows: S322. According to the stability theorem of the replication dynamic equation: like Recorded as but Whatever proportion of standardized information sharing an overseas logistics company decides to conduct is a stable strategy that will not change over time; like Let F(y) = 0, indicating that y = 0 and y = 1 are two equilibrium points; when hour, is the stable point in the evolution path analysis, that is, the proportion of domestic logistics enterprises that decide to share standardized information is higher than When foreign logistics companies decide to share standardized information; when hour, is the stable point in the evolution path analysis, that is, the proportion of domestic logistics enterprises choosing information sharing is lower than When foreign logistics companies decide not to share standardized information; S33. Analysis of the evolution path of domestic logistics enterprises: S331. Establish the replication dynamic equation of the information sharing strategy of the maritime transport logistics enterprise as follows: S332. According to the stability theorem of the replication dynamic equation: like but Domestic logistics enterprises have a stable strategy regardless of the proportion of information sharing they choose; like Let F(z) = 0, indicating that z = 0 and z = 1 are two equilibrium points; when hour, is the stable point in the evolution path analysis, that is, the proportion of overseas logistics enterprises choosing information sharing is higher than When domestic logistics companies decide to share standardized information; when hour, As the stable point in the evolution path analysis, the proportion of information sharing selected by overseas logistics enterprises is lower than At that time, domestic logistics companies decided not to share standardized information in order to avoid losses.

5. The method for improving the stability of a maritime logistics alliance based on blockchain according to claim 1, characterized in that: Step S4 specifically includes: S41. According to the replication dynamic equation in step S3, the Jacobian matrix of the tripartite replication dynamic system is derived as follows: S42. Let F(x)=F(y)=F(z)=0, and the local equilibrium points are E1(0,0,0), E2(0,0,1), E3(0,1,0), E4(0,1,1), E5(1,0,0), E6(1,0,1), E7(1,1,0), E8(1,1,1). If the eigenvalue of the Jacobi matrix is ​​negative, the local equilibrium point is an evolutionary stable strategy. S43. The application of blockchain platform makes the benefits of information sharing of alliance members greater than the benefits of not sharing. S44. Based on step S43, two assumptions are proposed as follows: Hypothesis 1: When only two parties choose to share, the overall benefits of the alliance are greater than the benefits of not sharing, that is: Assumption 2: When only one party chooses to share, the normal income of the members is higher than the income of the alliance chain, that is: (π i +ωλ i μ+Mθ i -C i )<π i -T i ; S45. Based on the assumptions in step S44, the local stability analysis results of the three-party evolutionary game of the alliance are obtained. From the perspective of maximizing the interests of the alliance members, E8 (1,1,1) is a strategy that is beneficial to all three game entities, that is, all alliance members choose the information sharing strategy.

6. A method for improving the stability of a maritime logistics alliance based on blockchain according to claim 1, characterized in that: Step S5 specifically includes: S51. Considering logistics risk, input resource value, information contribution and logistics stability, a modified Shapley value model is established as follows: F i '=Φ i +v(τ)(ω) i -1 / n) Φ'=(Φ1',Φ2',...,Φ n ') Where v(τ) is the total revenue of the entire shipping logistics alliance, Φ represents the original benefit obtained under the standard Shapley value model; Φ'=(Φ1',Φ2',...,Φ n ') represents the benefit distribution of the modified Shapley value method; ω i is the comprehensive benefit distribution influencing factor of the i-th alliance member, representing the sum of the four factors of the correction calculated according to a certain proportion weight; f j , j = 1, 2, 3, 4 are the weights of the above-mentioned 4 modified benefit distribution influencing factors. The weight coefficients of the influencing factors are obtained by consulting managers in the shipping logistics industry and related experts using the hierarchical analysis method; S52, determine the correction factor parameters: S521. Determine the value of input resources: Assume that the maritime logistics alliance has n members and invests m resources in total. P represents the value of resources invested by members. Assume that the correction coefficient of the value of invested resources is C, and K represents the resource value impact coefficient. The value of K depends on the role of the resource in the alliance. K<0 indicates that the investment of the resource has a negative effect on the output of the alliance's interests. Calculate the input resource market value matrix as follows: Calculate the input resource market value correction coefficient matrix as follows: Calculate the input resource value matrix as follows: Let E = [1 1...1] 1n , then calculate the impact factor θ of the benefit distribution of member i's input resource value i ,as follows: S522. Determine risk factors: Assume that the total number of members of the maritime logistics alliance is n, ΔR represents the value of logistics risk factors, r represents the risk factor benefit distribution influencing factor; R i '1' indicates the risk capability of members after joining the alliance, R i '1 represents the risk capacity of members before joining the alliance; R i '2' indicates the risk capacity of the alliance after the member joins, R i '2 represents the risk capacity of the alliance before joining the member; Calculate the change value ΔR of alliance members’ risk factors i ,as follows: ΔR i =ΔR i1 -ΔR i2 Among them, ΔR i1 =R i '1'-R i '1, ΔR i2 =R i '2'-R i '2; Calculate the risk factor benefit distribution impact factor r of member i i ,as follows: S523. Determine logistics: Assume that the total number of members of the maritime logistics alliance is n, ΔS represents the logistics stability measurement value, S represents the influencing factor of logistics stability benefit distribution; S i '1' indicates the logistics stability level of the member after joining the alliance, S i '1 represents the logistics stability level of the members before joining the alliance. i '2' indicates the logistics stability level of the alliance after joining the member, S i '2 represents the logistics stability level of the alliance before joining the member; Calculate the change measurement value ΔS of the logistics stability factor of alliance members as follows: in, Calculate the impact factor S of the logistics stability factor benefit distribution of member i i ,as follows: S524. Determine the information contribution of alliance members: Assume that information contribution is U, and the information contribution of logistics members is related to the data verification service A, shared information B, and maintenance node C provided by logistics members. According to the calculation of information contribution by blockchain technology and the advice of experts, the weights of providing data verification service A, sharing information B, and maintaining node C are set at 0.4, 0.3, and 0.3 respectively. Calculate the information contribution U for new alliance members i1 ,as follows: U i1 =A i1 ×0.4+B i1 ×0.3+C i1 ×0.3 Calculate the information contribution U of the alliance after the new member joins i2 ,as follows: U i2 =A i2 ×0.4+B i2 ×0.3+C i2 ×0.3 Calculate the alliance member information contribution change measurement value ΔU as follows: ΔU=U i1 -U i2 =0.4(A i1 -A i2 )+0.3(B i1 -B i2 )+0.3(C i1 -C i2 ) Calculate member i's information contribution and benefit distribution impact factor u i ,as follows: The modified Shapley value method can not only reflect the role played by alliance members in the process of maritime logistics transportation, but also obtain the best distribution plan of alliance benefits.

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