An industrial alliance-based park cross-regional investment attraction resource sharing system and method

Abstract

This invention discloses a cross-regional investment promotion resource sharing system and method based on industry alliances, relating to the technical fields of park investment promotion and consortium blockchain data sharing. The system comprises five modules: industry alliance node management, spatiotemporal value quantification of investment promotion resources, credit-anchored matching, a distributed encrypted resource pool, and smart contracts for revenue sharing upon successful implementation. It dynamically calculates the comprehensive value of resources by constructing a spatiotemporal value quantification model, achieves multi-dimensional accurate matching by combining alliance credit scores and industry distance, and employs an encrypted policy attribute-based encryption architecture of "index on-chain, details local" to ensure data sovereignty. Automatic revenue sharing and notarization upon successful implementation are achieved through consortium blockchain smart contracts. This invention overcomes the trust bottleneck and incentive deficiency pain points in cross-regional investment promotion resource sharing and can be widely applied to cross-administrative region park collaborative investment promotion scenarios led by industry alliances.

Description

Technical Field

[0001] Technical Field This invention relates to the fields of industrial park operation, investment promotion, and permissioned consortium blockchain data sharing, and particularly to a cross-regional investment promotion resource sharing system and method based on industrial alliances. It is primarily applied to scenarios of collaborative investment promotion, reliable sharing of investment promotion resources, and automatic distribution of benefits within industrial alliances across administrative regions. Keywords: industrial park investment promotion, industrial alliance, resource sharing. Background Technology

[0002] With the acceleration of regional economic integration, cross-regional industrial collaboration has become a core approach to optimizing industrial layout and improving investment attraction efficiency. Industrial alliances, as organizational vehicles for cooperation between industrial parks, provide an institutional foundation for resource sharing in cross-regional investment attraction.

[0003] Currently, existing technologies have not yet formed a mature and reliable technology implementation solution. For example, CN118761562B discloses a smart investment promotion method, intelligent investment promotion platform and storage medium for industrial parks. This solution improves the intelligence level of investment promotion in a single industrial park by constructing enterprise profiles and park profiles and matching investment promotion based on the similarity of industry tags. This solution has the following core defects: (1) It uses a centralized database to store all investment promotion data, without considering the data sovereignty claims of cross-regional parks. In cross-regional scenarios, parks are worried about the leakage of core business information and have a very low willingness to share high-quality resources; (2) The matching logic is based only on the static similarity of industry tags, without considering the time decay characteristics of investment promotion resources, and without incorporating the credit level of resource providers into the matching logic, resulting in insufficient reliability of the matching results; (3) It does not establish a benefit distribution mechanism for cross-park resource sharing, and cannot form a long-term sharing incentive. It is only applicable to investment promotion within a single industrial park and cannot support cross-regional collaboration under an industry alliance. For example, CN115545380A discloses a smart park integrated operation and maintenance management platform. This platform sets up an industry resource sharing platform unit to realize online collection and retrieval of information on enterprises in the park and industry service resources, supporting resource sharing and scheduling within a single park. This solution is a centralized operation and maintenance architecture for a single park, and does not involve cross-regional industry alliance collaboration scenarios. It only realizes basic information display and keyword retrieval, and does not conduct value quantification assessment of investment resources, thus failing to support accurate matching across parks. Another example is the paper "Investment Promotion and Operation Strategies of State-owned Enterprise Industrial Parks from the Perspective of Industrial Chain Collaboration" published in *China Science and Technology Investment*, authored by Gao Lin. This paper analyzes the advantages and practical difficulties of industrial chain collaborative investment promotion and proposes an institutional framework and strategic suggestions for collaborative investment promotion in parks under industrial alliances. This paper only stays at the qualitative discussion level of management, without providing a feasible technical implementation solution. It does not address core technical issues such as value quantification of investment resources, reliable data interaction, and automatic profit sharing, and fails to solve the three substantive technical pain points in cross-regional sharing: trust bottlenecks, inefficient matching, and lack of incentives.

[0004] In summary, the existing technologies generally have the following technical defects, which constitute the core problems to be solved by this invention: (1) The centralized architecture has a trust bottleneck: all investment promotion resource data is stored centrally, and cross-regional parks worry about the leakage of core customer information and investment promotion strategies. The willingness to share high-quality resources is low, the problem of information silos is prominent, and the organizational advantages of industry alliances cannot be implemented through technical means. (2) The value of resources lacks a quantitative evaluation system: only static information registration of investment promotion resources is carried out, without considering the dynamic value changes of resource timeliness, industry adaptability, and implementation potential. Matching relies on manual experience screening, which is inefficient and inaccurate, and cannot support large-scale cross-regional sharing. (3) The matching mechanism is single in dimension and lacks reliability: the existing matching is only based on industry labels and does not include the credit level of resource providers in the matching logic. False resources and low-quality information cannot be effectively filtered, the cost of cross-regional connection verification is high, and the reliability of resources is difficult to guarantee. (4) There is a lack of technical benefit distribution mechanism: the existing sharing model is mostly a one-time information payment. Resource providers cannot share the long-term benefits after the project is implemented. Moreover, the distribution process is not transparent, the settlement cycle is long, and the performance is not guaranteed, which cannot form a sustainable sharing ecosystem. Summary of the Invention

[0005] This invention provides a cross-regional investment promotion resource sharing system and method based on industry alliances. The specific technical problems it aims to solve are: overcoming the trust bottleneck in cross-regional investment promotion resource sharing, enabling cross-regional retrieval and sharing of investment promotion resources without disclosing core business data of the industrial park; establishing a dynamic and quantifiable investment promotion resource value assessment system to objectively reflect the timeliness and implementation potential of resources; constructing a multi-dimensional trustworthy matching mechanism that considers industry adaptability, resource value, and the creditworthiness of the provider, thereby improving the effectiveness of cross-regional connections; and forming a coded, automatically executable long-term revenue distribution mechanism to ensure reasonable returns for resource providers and build a sustainable sharing ecosystem.

[0006] To solve the above-mentioned technical problems, the present invention is achieved through the following technical solution:

[0007] This invention discloses a cross-regional investment promotion resource sharing system and method based on industry alliances. The core innovative idea of ​​this invention is as follows: using industry alliances as the organizational carrier and a permissioned consortium blockchain as the underlying trust foundation, it employs a CP-ABE distributed encrypted architecture of "index on-chain, details local" to safeguard data sovereignty from the ground up; it pioneers a spatiotemporal value quantification model for investment promotion resources, achieving dynamic and scientific quantification of resource value; it designs a credit-anchored matching algorithm, integrating the alliance credit system and industry distance quantification methods into the matching logic; it deploys on-chain profit-sharing smart contracts to achieve automatic and reliable distribution of project revenue; ultimately forming a complete technical closed loop of "node access - value quantification - precise matching - encrypted interaction - profit sharing - credit iteration". This solution is not a simple aggregation of existing technologies: the distributed encrypted architecture solves the problem of resource supply willingness, the spatiotemporal value model solves the problem of scientific resource assessment, the credit-anchored matching solves the problem of matching accuracy and reliability, and the smart contract profit sharing solves the problem of long-term incentives. These four technical means support and synergize with each other to jointly solve the systemic problem of cross-regional investment promotion sharing in industry alliances, rather than a single-point improvement of a single technical problem.

[0008] A cross-regional investment promotion resource sharing system for industrial parks based on industry alliances includes an industry alliance node management module that is sequentially connected by signals to realize data interaction, an investment promotion resource spatiotemporal value quantification module, a credit anchoring and matching module, a distributed encrypted resource pool module, and a landing-based profit-sharing smart contract module deployed on the underlying layer of the industry alliance's permissioned alliance chain.

[0009] The industry alliance node management module has a built-in qualification review unit, credit score calculation unit and permission configuration unit. The qualification review unit is used to verify the qualifications of park nodes applying to join the industry alliance. The credit score calculation unit is used to calculate the dynamic credit score of the node based on three dimensions: resource authenticity rate, historical implementation contribution rate and resource response timeliness. The permission configuration unit is used to allocate corresponding data access and resource publishing permissions according to the node's credit score level.

[0010] The spatiotemporal value quantification module for investment resources includes an attribute extraction unit, a parameter calibration unit, and a value calculation unit. The attribute extraction unit extracts three basic attributes from the uploaded investment resources: investment scale, industry category, and willingness to invest, generating structured attribute data. The industry category is automatically mapped to the fourth-level code of the National Economic Industry Classification Standard (GB / T4754-2017). The parameter calibration unit is used to calibrate the initial benchmark value, time decay coefficient, industry fit coefficient, and investment conversion probability coefficient for the corresponding attributes. The value calculation unit calculates the current comprehensive value of the investment resources using a preset spatiotemporal value quantification formula and generates standardized resource tags.

[0011] The credit anchoring and matching module is the core of the system's matching decision. It calls the credit score data from the node management module and the value data from the value quantification module to achieve multi-dimensional accurate matching. It has three core units built in.

[0012] Demand Analysis Unit: Analyzes the investment promotion needs released by the target park, extracts rigid thresholds such as the main industry direction, minimum investment scale, and land use requirements, and first performs an initial screening: filters out resources with investment scales below the threshold and industry distances greater than 8, thus narrowing down the candidate range;

[0013] Industry Distance Calculation Unit: Based on the four-level system of the National Economic Industry Classification Standard (GB / T4754-2017), the industry distance is quantitatively calculated, replacing the traditional label similarity and more accurately depicting the degree of industry fit.

[0014] The credit-anchored matching module incorporates a demand analysis unit, an industry distance calculation unit, and a matching degree ranking unit. The demand analysis unit analyzes the investment attraction needs of the target park and extracts industry direction and scale threshold requirements. The industry distance calculation unit calculates the industry distance between the resource's industry and the target park's leading industry based on the National Economic Industry Classification Standard. The matching degree ranking unit calculates the matching degree score by combining the resource's current comprehensive value, the resource provider's credit score, and the industry distance, and outputs the matching results in descending order of score. The matching degree ranking unit uses the resource's comprehensive value as a basis, multiplies it by the provider's credit score, divides it by the industry distance to obtain the final matching degree score, and outputs the matching results in descending order of score. This algorithm simultaneously considers resource value, credit reliability, and industry adaptability, overcoming the limitations of existing single-dimensional matching technologies.

[0015] The distributed encrypted resource pool module is the data security foundation of the system. It is built using a policy-based encryption (CP-ABE) architecture and has built-in on-chain index storage unit and local detail storage unit. The on-chain index storage unit is used to encrypt non-sensitive index information such as the comprehensive value, tags, and industry codes of resources and store it on the distributed nodes of the consortium blockchain after encryption using CP-ABE. All consortium nodes synchronously store the encrypted index. The access policy is set to "credit level ≥ B and industry category matching". Nodes that meet the attribute can decrypt and view the index information themselves, but cannot obtain the details. The local detail storage unit is used to store core sensitive data such as enterprise contact information, specific investment plans, and site selection requirements on the local node server of the resource provider. It is not uploaded to any centralized server or consortium blockchain, thus ensuring data sovereignty from the source.

[0016] Access control logic: The encryption master key is uniformly generated and managed by the industry alliance root node and is used to generate system attribute keys; after obtaining the matching list, if the requester needs to view the details, it must initiate a details access request to the provider; after the provider verifies the requester's qualifications, it issues the details decryption key to the requester point-to-point; the decryption operation is only completed locally on the requester's site, and the details data is not transmitted across nodes, realizing that the data is "usable but not visible, authorized but accessible".

[0017] The core of the incentive closed loop of the landing and profit-sharing smart contract module system is deployed on the industry alliance's permissioned consortium blockchain. The contract code is publicly available throughout the alliance and its execution is tamper-proof. It has three core units: a landing verification unit, a profit-sharing execution unit, and a proof storage unit. The landing verification unit connects to the National Enterprise Credit Information Publicity System and local tax public data interfaces, cross-compares the project's business registration address, tax registration information, and unified social credit code, and automatically verifies the authenticity of the project's landing without manual intervention. The verification results are simultaneously uploaded to the blockchain for proof storage. Once the profit-sharing execution unit verifies the transaction, the preset profit-sharing rules are automatically triggered. The profit-sharing model uses the investment promotion points uniformly issued by the alliance as the on-chain accounting unit, with 1 investment promotion point pegged to 1 RMB. When distributing profits, the corresponding points are automatically transferred to the resource provider's on-chain account. At the end of each month, each node can apply for fiat currency redemption from the alliance's co-managed account based on its on-chain point balance, ensuring that the flow of funds is compliant and traceable. The evidence storage unit is used to store project implementation information, profit-sharing amount, and distribution results on the blockchain throughout the entire process, which is tamper-proof and traceable. At the same time, it sends update instructions to the credit score calculation unit of the industry alliance node management module to adjust the credit score of the resource provider synchronously, completing the credit iteration closed loop.

[0018] Furthermore, the credit score calculation formula of the credit score calculation unit is as follows:

[0019]

[0020] In the formula, The node's dynamic credit score ranges from 0 to 1. Resource authenticity rate, which is the ratio of the number of resources actually deployed to the total number of resources published at that node within the statistical period; Contribution rate to historical implementation, which is the percentage of resources provided by this node that were ultimately successfully implemented within the statistical period; Resource response timeliness is categorized based on the response time after the requester initiates an access request. , , Let be the weighting coefficient, satisfying + + =1, default value is =0.4、 =0.4、 =0.2; The initial credit score of a node is 0.6. The credit score increases after the node completes genuine resource sharing and the project is implemented. The credit score is deducted when false resources are published.

[0021] Furthermore, the spatiotemporal value quantification formula of the value calculation unit is:

[0022] ;

[0023] In the formula, The current comprehensive value of the investment resources is represented by a dimensionless comprehensive score. The initial benchmark value of the resource is determined by the investment scale corresponding to the resource and tiered accordingly. This is the time decay coefficient, ranging from 0.01 to 0.05 per day. It is dynamically adjusted according to the industry type of the resource. It is dynamically set according to industry type. Manufacturing projects have a long window of implementation and slow decay, while service industry and science and technology innovation projects have a short window of implementation and fast decay. The value is based on the following: the average window of implementation for manufacturing projects is about 60-90 days, corresponding to a cycle of decay to 10% of the initial value; the average window of implementation for science and technology innovation projects is about 20-30 days, corresponding to a decay cycle. The number of days between the time the resource was published and the current time; The industry fit coefficient ranges from 0 to 1, representing the degree of fit between resources and the local leading industries of resource providers. It is determined according to the industry distance between resource industries and local leading industries: 1.0 for the same sub-category, 0.8 for the same medium-sized category, 0.6 for the same major category, 0.3 for the same sector, and 0.1 for different sectors. The probability coefficient for implementation and conversion ranges from 0 to 1. It is based on the historical implementation rate of similar resources. When historical data of the alliance exists, it is the number of implementations of resources of the same industry category in the past 12 months / the total number of connections. When there is no historical data, it is graded according to the intensity of the willingness to implement: 0.8 for strong willingness, 0.5 for medium willingness, and 0.3 for weak willingness.

[0024] The value calculation unit calculates the current comprehensive value of resources in real time using a spatiotemporal value quantification formula; it also generates standardized resource tags simultaneously, providing a quantitative basis for subsequent matching. This value calculation unit's spatiotemporal value quantification formula is the first to incorporate the time decay effect into the valuation of investment resources, aligning with the industry characteristic of limited investment window periods; a lower limit of 0.1 is set to prevent resources from becoming completely unsearchable after their value reaches zero.

[0025] The parameter calibration unit completes parameter calibration based on structured attributes; initial reference value. The investment scale is categorized as follows: less than 100 million yuan corresponds to 20, 100-500 million yuan corresponds to 60, 500-1 billion yuan corresponds to 100, and more than 1 billion yuan corresponds to 150. This is a dimensionless comprehensive score, used only for relative value comparison.

[0026] Furthermore, the matching degree calculation formula for the matching degree ranking unit is as follows:

[0027]

[0028] In the formula, A score is given for the matching degree between resources and target parks; The current comprehensive value of the resources; Alliance credit score for resource providers; This represents the industrial distance between the industry to which the resource belongs and the dominant industry of the target park, with a value ranging from 1 to 10. The higher the degree of industrial overlap, the smaller the value.

[0029] Furthermore, the distributed encrypted resource pool module adopts an encrypted policy attribute-based encryption scheme, and the access policy of the resource index is bound to the industry attributes and credit rating of the demand node; the encryption master key is uniformly generated and distributed by the root node of the industry alliance, and the decryption key of the resource detail data is distributed point-to-point from the resource provider node to the authorized demand node. The decryption operation is only completed locally on the demand node, and the detail data is not transmitted through a centralized server throughout the entire process.

[0030] Furthermore, the triggering condition for the landing profit-sharing smart contract module is as follows: after the project completes business registration and tax registration in the target park, and the landing verification unit cross-compares the business entity information and tax registration information to confirm their authenticity and validity, the profit-sharing execution unit is automatically triggered; the profit-sharing ratio is preset by the resource provider and the demand party through an on-chain contract before resource docking, supporting two distribution modes: fixed ratio and tiered ratio. The tiered ratio mode sets the profit-sharing ratio according to the investment scale of the project landing, and the higher the investment scale, the higher the profit-sharing ratio of the resource provider.

[0031] Furthermore, after the landing verification unit verifies the authenticity of the project landing, it sends a credit enhancement instruction to the credit score calculation unit; if the verification finds that the resource has false information, the credit score calculation unit deducts 0.2 credit points from the corresponding node at once. When the credit score is lower than 0.3, the permission configuration unit restricts the resource publishing permission of that node.

[0032] Permission configuration unit: Based on the node credit score, four levels are defined: 0.8 and above is Level A, 0.5-0.8 is Level B, 0.3-0.5 is Level C, and below 0.3 is Level D. Level A nodes enjoy the highest access priority and unlimited resource publishing permissions, Level B nodes enjoy regular permissions, Level C nodes are limited to a maximum of 5 resource publishings per day, and Level D nodes have suspended resource publishing permissions. This hierarchical permission system forms a positive incentive constraint. Node credit level synchronization is one of the core attributes of CP-ABE encryption.

[0033] Furthermore, the parameter calibration unit dynamically sets the time decay coefficient according to the industry type. Manufacturing projects Values ​​range from 0.01 to 0.02 per day for modern service industries and science and technology innovation projects. The value ranges from 0.03 to 0.05 per day.

[0034] Furthermore, the industry distance calculation unit calculates industry distance based on the four-level standard of the National Economic Industry Classification: category-major category-intermediate category-minor category. When the resource industry and the target park's leading industry belong to the same minor category... =1, when different subcategories are within the same subclass. =2, when different subcategories are within the same major category =4, different major categories within the same category =7, different categories =10; When the target industrial park has multiple leading industries, the minimum value of the distance between the corresponding industries of all leading industries is taken as the final value. value.

[0035] A method for cross-regional investment promotion and resource sharing in industrial parks based on industry alliances, implemented using the aforementioned system, includes the following steps:

[0036] S1. Node Admission and Initialization: Parks applying to join the industry alliance submit qualification materials. After passing the qualification review unit, they become alliance nodes. The credit score calculation unit allocates initial credit scores, and the permission configuration unit allocates corresponding on-chain accounts and initial permissions.

[0037] S2. Resource Upload and Value Quantification: Park nodes upload local investment resources, attribute extraction unit extracts core resource attributes, parameter calibration unit completes parameter assignment, and value calculation unit calculates the current comprehensive value and generates resource tags through spatiotemporal value quantification formula; encrypted resource index is uploaded to on-chain index storage unit, and resource details are stored in local detail storage unit.

[0038] S3. Demand Release and Intelligent Matching: The target park releases its investment promotion needs. The demand parsing unit extracts the demand parameters and completes the initial screening. The industry distance calculation unit calculates the industry distance of each candidate resource. The matching degree ranking unit calculates the score through the matching degree formula and outputs the matching list in descending order.

[0039] S4. Encrypted Resource Interaction and Integration: After the requester selects the target resource, it initiates a detailed access request. After the permission verification is passed, it obtains the decryption key, decrypts and views the resource details on the local node, and the two parties conduct offline integration.

[0040] S5. Project Implementation and Profit Sharing Evidence Storage: After the project is implemented, the implementation verification unit cross-verifies the authenticity of the implementation information. Once the verification is passed, the profit sharing execution unit is triggered to complete the automatic transfer of income. The evidence storage unit will put the entire process data on the blockchain for evidence storage and update the dynamic credit score of the corresponding node in a synchronous manner.

[0041] The present invention has the following advantages over the prior art:

[0042] (1) Breaking the cross-regional sharing trust bottleneck from the architecture level: Adopting a distributed encrypted resource pool architecture of "index on chain, details local" and combining attribute-based encryption fine-grained access control, the data sovereignty and business secret security of each park are guaranteed from the technical level. It does not need to rely on the endorsement of a third-party centralized platform, which can effectively stimulate the willingness of parks within the alliance to supply high-quality resources, alleviate the problem of investment promotion information silos from the root, and enable the organizational advantages of the industry alliance to be truly implemented through technical means.

[0043] (2) The first time a time-space value quantification model was created to realize dynamic assessment of resource value: For the first time, the time decay effect, industry adaptability and landing conversion probability were incorporated into a unified quantitative framework to construct a time-space value quantification formula for investment promotion resources with boundary constraints, replacing the traditional static resource information registration model. It can dynamically reflect the real-time value changes of investment promotion resources, which is in line with the industry characteristics of investment promotion projects having a time window period. It provides an objective and quantifiable assessment basis for cross-regional resource matching and significantly improves the scientific nature of matching decisions.

[0044] (3) Credit anchoring matching algorithm, taking into account both efficiency and reliability: a multi-dimensional matching algorithm is proposed, which integrates the dynamic credit system of the industry alliance and the four-level industry distance quantification method into the matching logic. It not only filters out low-quality and false resources through credit weight, reducing the verification cost and ineffective investment in cross-regional docking, but also accurately describes the degree of industry compatibility through standardized industry distance, realizing the optimal matching of resource value, credit reliability and industry compatibility in multiple dimensions, and improving the efficiency of cross-regional investment promotion docking;

[0045] (4) Smart contract profit-sharing mechanism to build a long-term sharing closed loop: Based on the deployment of code-based smart contracts for profit sharing in the consortium blockchain, the rules are transparent and open, the execution is immutable, and the settlement is completed automatically. This solves the pain points of opaque profit distribution, long settlement cycle, and lack of performance guarantee in traditional cross-regional investment promotion and sharing. It allows resource providers to stably share the long-term benefits after the project is implemented, and builds a positive cycle incentive mechanism of "resource sharing - value realization - credit iteration" to ensure the sustainable operation of the sharing ecosystem.

[0046] (5) Systemic innovation rather than simple technology superposition: This solution forms a complete technical closed loop from the underlying data architecture, core value algorithm, matching decision logic to incentive distribution mechanism. It is not a simple combination of existing investment promotion system, blockchain technology and matching algorithm. It proposes an integrated systemic technical solution to address the three core pain points of trust, efficiency and incentive that have long existed in the cross-regional investment promotion scenario of industry alliances. The technical features of each technology work together to produce superimposed technical effects.

[0047] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0048] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0049] Figure 1 This is an overall architecture diagram of the cross-regional investment promotion and resource sharing system for industrial parks based on industry alliances as described in this invention;

[0050] Figure 2 This is a flowchart illustrating the process of quantifying the spatiotemporal value of investment resources in this invention.

[0051] Figure 3 This is a schematic diagram of the execution flow of the credit anchoring matching algorithm of the present invention;

[0052] Figure 4 This is a schematic diagram illustrating the execution process of the profit-sharing smart contract implemented in this invention. Detailed Implementation

[0053] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0054] Terminology Definitions: All technical terms used in this specification are defined uniformly upon their first appearance, and should be clearly understood by those skilled in the art.

[0055] Permissioned consortium blockchain: a distributed ledger technology where only authorized nodes that have passed audits can access the network and participate in data consensus. Data is only synchronized among consortium nodes and is not publicly visible, making it suitable for multi-institutional collaboration scenarios. In this solution, the consortium blockchain consensus mechanism adopts the industry-standard Practical Byzantine Fault Tolerance (PBFT) algorithm to ensure data consistency among nodes.

[0056] Ciphertext Policy Attribute Base Encryption (CP-ABE): An asymmetric encryption technique that sets an access policy during encryption, allowing only users whose attribute set satisfies the access policy to decrypt the ciphertext; used in this scheme for fine-grained access control of resource indexes.

[0057] Industry distance: Based on the four-level classification system of the National Economic Industry Classification Standard (GB / T4754-2017), it is a numerical value that quantitatively represents the degree of upstream and downstream correlation and overlap between two types of industries. The smaller the value, the stronger the industry compatibility.

[0058] Investment resources: refers to the information on enterprises and projects that the park has in its possession that have the intention to relocate or expand their production capacity, including core elements such as investment scale, industry category, and site selection requirements.

[0059] Example 1:

[0060] This example demonstrates a cross-regional investment promotion scenario within the Yangtze River Delta High-end Manufacturing Industry Alliance. The alliance comprises three national-level industrial parks: Suzhou Industrial Park, Ningbo Beilun Economic Development Zone, and Wuxi High-tech Zone. Each park serves as a node in the alliance's blockchain and is connected to this system. The alliance's underlying layer uses a permissioned blockchain with a PBFT consensus mechanism for data consensus and synchronization among nodes. The alliance has one root node responsible for master key management and final qualification review. Each park deploys its own business module servers locally.

[0061] Step S1: Node Admission and Initialization:

[0062] The three parks submitted their park qualification documents and leading industry certification materials. After verification by the qualification review unit of the industry alliance node management module, all three met the alliance access standards and officially became alliance nodes.

[0063] The credit score calculation unit assigns an initial credit score (S=0.6) to each node, corresponding to Level B permissions; the permission configuration unit assigns on-chain accounts and basic permissions to each node, enabling them to publish resources, view resource indexes, and initiate access requests; and simultaneously generates industry attribute tags for each node.

[0064] Among them, the leading industry of Suzhou Industrial Park is general equipment manufacturing (GB / T4754-2017 code C34), the leading industry of Ningbo Beilun Economic Development Zone is auto parts and accessories manufacturing (C367), and the leading industries of Wuxi High-tech Zone are general equipment manufacturing (C34) and electronic component manufacturing (C397).

[0065] Step S2: Resource Upload and Value Quantification

[0066] A business opportunity was posted on the Ningbo Beilun Economic Development Zone website: A car chassis parts company plans to relocate and invest 500 million yuan, with an annual output value of 1.2 billion yuan. The company belongs to the category of car parts and accessories manufacturing (C367). The company has clearly expressed its willingness to settle in the area. The day the resource was posted is recorded as day 0.

[0067] The module for quantifying the spatiotemporal value of investment resources performs the following operations:

[0068] (1) The attribute extraction unit extracts the core attributes: investment scale of 500 million yuan, industry category C367, strong willingness to settle down, and automatically maps to the national standard level 4 code.

[0069] (2) The parameter calibration unit completes parameter assignment:

[0070] An investment of 500 million yuan falls within the 500 million to 1 billion yuan range, and an initial benchmark value is set. =100 (dimensionless score).

[0071] The project belongs to the manufacturing industry, and the time decay factor is... A value of 0.015 / day is used (fitting the manufacturing sector's range of 0.01~0.02, matching a landing window of approximately 60 days); the resource industry is completely consistent with Ningbo's leading local industries (within the same sub-category), resulting in an industry fit coefficient of... =1.0; Strong willingness to implement, calibrated conversion probability coefficient. =0.8.

[0072] (3) The value calculation unit calculates the current comprehensive value of the resource on the 10th day after its release. =10, substituting into the formula for quantifying the value of spacetime:

[0073] ;

[0074] The system generates standardized resource tags: auto parts, 500 million yuan investment, high willingness to be implemented. The index information such as value, tag, and industry code is encrypted with CP-ABE and uploaded to the on-chain index storage unit. The access policy is set to "credit rating ≥ B and industry category = manufacturing". Detailed data such as enterprise contact information, specific site selection requirements, and output value targets are stored in the local detailed storage unit of the Ningbo node and are not transmitted to the outside.

[0075] Step S3: Demand Posting and Intelligent Matching

[0076] Wuxi High-tech Zone has released its investment promotion requirements: to introduce high-end equipment and upstream and downstream supporting enterprises with an investment scale of over 300 million yuan.

[0077] The credit anchoring matching module performs the following operations:

[0078] (1) The demand analysis unit extracts demand parameters: industry direction: high-end equipment manufacturing, minimum investment scale of 300 million yuan; perform initial screening to filter resources with investment scale of less than 300 million yuan and industry distance greater than 8.

[0079] (2) Calculation of industry distance using industry distance calculation unit: Wuxi High-tech Zone has two leading industries, namely general equipment manufacturing (C34) and electronic component manufacturing (C397); resource industry is C367, which belongs to the same manufacturing category as C34 but is a different subcategory, corresponding to an industry distance of 7; it belongs to the same manufacturing category as C397 but is a different subcategory, corresponding to an industry distance of 7; the minimum value is taken as the final industry distance. =7.

[0080] (3) The matching degree sorting unit calls the current credit score of the Ningbo node. =0.75, substituting into the matching degree formula: ;

[0081] The system iterates through all resources that meet the initial screening criteria, calculates the matching score for each resource, sorts them in descending order of score, and outputs the matching results list to Wuxi High-tech Zone when the resource is ranked in the top three.

[0082] Step S4: Encrypted resource interaction and integration:

[0083] After reviewing the matching list, Wuxi High-tech Zone initiated a request to access the detailed data of the auto parts resource.

[0084] The permission configuration unit verifies that Wuxi High-tech Zone's credit rating is B and its industry attribute is manufacturing, meeting the index access policy, and then pushes the application to the Ningbo node. The Ningbo node reviews Wuxi High-tech Zone's eligibility for connection, and after confirmation, issues the detailed decryption key to the Wuxi node point-to-point.

[0085] The Wuxi node uses a decryption key to access the local detailed storage unit of the Ningbo node on its local server, obtaining core information such as the company's contact information and site selection requirements. Representatives from both parties then conduct offline negotiations. Throughout the process, core detailed data does not pass through any centralized platform; it is only decrypted and viewed peer-to-peer between authorized nodes, ensuring data security and sovereignty. Step S5: Project Implementation and Profit Sharing Evidence Storage

[0086] After three months of negotiations, the auto parts company finally completed its business registration and tax registration in Wuxi High-tech Zone, and the project was officially launched with an actual investment of 600 million yuan.

[0087] The landing-based profit-sharing smart contract module performs the following operations:

[0088] (1) The landing verification unit connects with the National Enterprise Credit Information Publicity System and the local tax public data, cross-compares the enterprise's registered address, tax registration information and unified social credit code, confirms the project's real landing, and passes the verification.

[0089] (2) The profit-sharing execution unit triggers the preset tiered profit-sharing rules: the two parties pre-agreed that the profit-sharing ratio is 25% for investments below RMB 500 million and 30% for investments between RMB 500 million and RMB 1 billion; the actual investment in this case is RMB 600 million, corresponding to a profit-sharing ratio of 30%, that is, the resource provider, Ningbo Beilun Economic Development Zone, will receive 30% of the local retention portion of the park's tax revenue in the first year of the project as shared income; the smart contract automatically calculates the profit-sharing amount, transfers the corresponding investment promotion points to the Ningbo node's on-chain account, and generates a storage hash on the chain.

[0090] (3) The evidence storage unit will store the project implementation information, profit sharing amount and distribution results on the blockchain throughout the entire process, which cannot be tampered with; at the same time, it will send a credit improvement instruction to the credit score calculation unit, and the credit score of the Ningbo node will be improved from 0.75 to 0.78, still at level B, completing the credit iteration closed loop; at the end of each month, the Ningbo node can apply for fiat currency redemption to the alliance co-managed account based on the on-chain points.

[0091] Example 2:

[0092] This embodiment uses the Guangdong-Hong Kong-Macao Greater Bay Area Science and Technology Innovation Industry Alliance as its platform, encompassing three parks: Shenzhen Nanshan Science and Technology Park, Dongguan Songshan Lake High-tech Zone, and Guangzhou Huangpu Development Zone. The leading industries are electronic information and biomedicine, with a focus on verifying the time decay boundary mechanism and credit constraint mechanism of the spatiotemporal value model.

[0093] Scenario 1: Verification of Time-Related Decay and Boundary Mechanisms

[0094] A biomedical science and technology innovation enterprise with an investment scale of 200 million yuan has been uploaded to the Shenzhen Nanshan Science and Technology Park node. It belongs to the science and technology innovation service industry and has a moderate willingness to settle in.

[0095] Parameter calibration unit assignment:

[0096] (1) An investment scale of 200 million yuan falls within the range of 100 million to 500 million yuan, with an initial benchmark value. =60;

[0097] (2) The project belongs to the science and technology innovation service industry category, and the time decay coefficient is... Take 0.04 / day (the window of opportunity for the implementation of science and technology innovation projects is short, which falls within the range of 0.03~0.05).

[0098] (3) Resource industries belong to the same major category as Shenzhen's local leading industries, and the industry fit coefficient is high. =0.6;

[0099] (4) Moderate willingness to implement, and a high probability coefficient of implementation conversion. =0.5.

[0100] Thirty days after the resource was released, the Guangzhou Huangpu Development Zone issued a request for investment in the biopharmaceutical industry. The system calculated the current comprehensive value of the resource. =30, substitute into the formula:

[0101] 1- =1-0.04 30 = -0.2;

[0102] Boundary constraints are triggered, with 0.1 as the lower limit. Therefore:

[0103] V=60 0.1 0.6 0.5 = 1.8;

[0104] Because the resource's release time far exceeds the typical window for science and technology innovation projects, its value decays to a lower limit, resulting in a significant decrease in its matching score. The system then places it lower on the matching list to avoid wasting effort on ineffective resources. This dynamic decay and boundary constraint mechanism is not present in existing static resource libraries; it automatically filters out expired and inefficient resources, improving the effectiveness of matching results.

[0105] Scenario 2: Validation of the credit constraint mechanism:

[0106] Suppose that the Dongguan Songshan Lake High-tech Zone node uploads a fake investment resource, falsely claiming that a certain electronics and information company has expressed investment intentions, when in fact there is no corresponding company. The Guangzhou Huangpu Development Zone, after contacting the node, discovers the resource is fake and files a complaint with the alliance.

[0107] The on-site verification unit cross-verifies with industrial and commercial data, confirms that the resource information is false, and sends a deduction instruction to the credit score calculation unit. The system deducts 0.2 credit points from the Dongguan node in one go, reducing the credit score from the initial 0.6 to 0.4, corresponding to C-level permissions; the permission configuration unit simultaneously restricts the node to posting a maximum of 5 resources per day and automatically reduces the credit weight of its resources in the matching calculation.

[0108] If a node's credit score continues to drop below 0.3, the system will automatically restrict its resource publishing permissions, thus ensuring the overall quality of the resource pool. This credit-anchored constraint mechanism is deeply integrated with the matching algorithm, a feature not found in existing centralized investment promotion platforms.

[0109] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A resource-sharing system and method for cross-regional investment promotion in industrial parks based on industry alliances, characterized in that, It includes an industry alliance node management module that connects sequentially with signals to realize data interaction, an investment promotion resource spatiotemporal value quantification module, a credit anchoring and matching module, a distributed encrypted resource pool module, and a landing-based profit-sharing smart contract module deployed on the bottom layer of the industry alliance permissioned alliance chain. The industry alliance node management module has a built-in qualification review unit, credit score calculation unit and permission configuration unit. The qualification review unit is used to verify the qualifications of park nodes applying to join the industry alliance. The credit score calculation unit is used to calculate the dynamic credit score of the node based on three dimensions: resource authenticity rate, historical implementation contribution rate and resource response timeliness. The permission configuration unit is used to allocate corresponding data access and resource publishing permissions according to the node's credit score level. The spatiotemporal value quantification module for investment resources includes an attribute extraction unit, a parameter calibration unit, and a value calculation unit. The attribute extraction unit extracts three basic attributes from the uploaded investment resources: investment scale, industry category, and willingness to invest. The parameter calibration unit calibrates the initial benchmark value, time decay coefficient, industry fit coefficient, and investment conversion probability coefficient for each attribute. The value calculation unit calculates the current comprehensive value of the investment resources using a preset spatiotemporal value quantification formula and generates standardized resource tags. The credit anchoring matching module has a built-in demand analysis unit, industry distance calculation unit, and matching degree ranking unit. The demand analysis unit is used to analyze the investment promotion needs of the target park and extract the industry direction and scale threshold requirements. The industry distance calculation unit calculates the industry distance between the industry to which the resource belongs and the leading industry of the target park based on the national economic industry classification standard. The matching degree ranking unit calculates the matching degree score by combining the current comprehensive value of the resource, the credit score of the resource provider, and the industry distance, and outputs the matching results in descending order of the score. The distributed encrypted resource pool module adopts an encrypted policy attribute-based encryption architecture, with built-in on-chain index storage unit and local detailed storage unit. The on-chain index storage unit is used to store the comprehensive value, resource tag, and industry category of the resource in the distributed nodes of the consortium chain after encryption. The local detailed storage unit is used to store the enterprise contact information and investment site selection details corresponding to the resource in the local node of the resource provider. Only the request node that has passed the permission verification can decrypt and view the detailed data. The landing and profit-sharing smart contract module is deployed on the industry alliance blockchain and has a built-in landing verification unit, profit-sharing execution unit and evidence storage unit. The landing verification unit is used to cross-verify the project landing status by connecting with public data from industry and commerce and taxation. After the verification is passed, the profit-sharing execution unit automatically executes the profit transfer according to the preset profit-sharing rules. The evidence storage unit is used to store the entire profit-sharing process data on the blockchain and update the credit score of the corresponding node in a synchronous manner.

2. The cross-regional investment promotion and resource sharing system for industrial parks based on industry alliances as described in claim 1, characterized in that, The credit score calculation formula of the credit score calculation unit is as follows: In the formula, The node's dynamic credit score ranges from 0 to 1. Resource authenticity rate, which is the ratio of the number of resources actually deployed to the total number of resources published at that node within the statistical period; Contribution rate to historical implementation, which is the percentage of resources provided by this node that were ultimately successfully implemented within the statistical period; Resource response timeliness is categorized based on the response time after the requester initiates an access request. , , Let be the weighting coefficient, satisfying + + =1, the default value is 1. =0.4、 =0.4、 =0.2; The initial credit score of a node is 0.

6. The credit score increases after the node completes genuine resource sharing and the project is implemented. The credit score is deducted when false resources are published.

3. The cross-regional investment promotion and resource sharing system for industrial parks based on industry alliances as described in claim 1, characterized in that, The spatiotemporal value quantification formula for the value calculation unit is: ； In the formula, The current comprehensive value of the investment resources is represented by a dimensionless comprehensive score. The initial benchmark value of the resource is determined by the investment scale corresponding to the resource and tiered accordingly. This is the time decay coefficient, with a value ranging from 0.01 to 0.05 per day, dynamically adjusted according to the industry type to which the resource belongs; The number of days between the time the resource was published and the current time; The industry fit coefficient, ranging from 0 to 1, represents the degree of fit between resources and the local leading industries of resource providers; The conversion probability coefficient is set at 0 to 1, based on the historical conversion rate of similar resources. The formula is set to 0.1 as the lower limit of value decay to prevent the value of resources from decaying to zero or negative over time.

4. A cross-regional investment promotion and resource sharing system for industrial parks based on industry alliances as described in claim 3, characterized in that, The matching degree calculation formula for the matching degree sorting unit is as follows: In the formula, A score is given for the matching degree between resources and target parks; The current comprehensive value of the resources; Alliance credit score for resource providers; This represents the industrial distance between the industry to which the resource belongs and the dominant industry of the target park, with a value ranging from 1 to 10. The higher the degree of industrial overlap, the smaller the value.

5. A cross-regional investment promotion and resource sharing system for industrial parks based on industry alliances as described in claim 1, characterized in that, The distributed encrypted resource pool module adopts an encrypted policy attribute-based encryption scheme. The access policy of the resource index is bound to the industry attributes and credit rating of the demand node. The encryption master key is uniformly generated and distributed by the root node of the industry alliance. The decryption key of the resource detail data is distributed point-to-point from the resource provider node to the authorized demand node. The decryption operation is only completed locally on the demand node. The detail data is not transmitted through a centralized server throughout the entire process.

6. A cross-regional investment promotion and resource sharing system for industrial parks based on industry alliances as described in claim 1, characterized in that, The triggering conditions for the landing and profit-sharing smart contract module are as follows: after the project completes business registration and tax registration in the target park, and the landing verification unit cross-compares the business entity information and tax registration information to confirm their authenticity and validity, the profit-sharing execution unit is automatically triggered; the profit-sharing ratio is preset by the resource provider and the demand party through an on-chain contract before resource docking, supporting two distribution modes: fixed ratio and tiered ratio. The tiered ratio mode sets the profit-sharing ratio according to the investment scale of the project landing, and the higher the investment scale, the higher the profit-sharing ratio of the resource provider.

7. A cross-regional investment promotion and resource sharing system for industrial parks based on industry alliances as described in claim 2, characterized in that, After verifying the authenticity of the project implementation, the landing verification unit sends a credit enhancement instruction to the credit score calculation unit. If the verification finds that the resource contains false information, the credit score calculation unit deducts 0.2 credit points from the corresponding node at once. When the credit score is lower than 0.3, the permission configuration unit restricts the resource publishing permission of that node.

8. A cross-regional investment promotion resource sharing system for industrial parks based on industry alliances as described in claim 3, characterized in that, The parameter calibration unit dynamically sets the time decay coefficient according to the industry type. Manufacturing projects Values ​​range from 0.01 to 0.02 per day for modern service industries and science and technology innovation projects. The value ranges from 0.03 to 0.05 per day.

9. A cross-regional investment promotion and resource sharing system for industrial parks based on industry alliances as described in claim 4, characterized in that, The industry distance calculation unit calculates industry distance based on the four-level standard of national economic industry classification: category-major category-intermediate category-minor category. When the resource industry and the target park's leading industry belong to the same minor category... =1, when different subcategories are within the same subclass. =2, when different subcategories are within the same major category =4, different major categories within the same category =7, different categories =10; When the target industrial park has multiple leading industries, the minimum value of the distance between the corresponding industries of all leading industries is taken as the final value. value.

10. A method for cross-regional investment promotion and resource sharing in industrial parks based on industry alliances, implemented using the system described in any one of claims 1-9, characterized in that, Includes the following steps: S1. Node Admission and Initialization: Parks applying to join the industry alliance submit qualification materials. After passing the qualification review unit, they become alliance nodes. The credit score calculation unit allocates initial credit scores, and the permission configuration unit allocates corresponding on-chain accounts and initial permissions. S2. Resource Upload and Value Quantification: Park nodes upload local investment resources, attribute extraction unit extracts core resource attributes, parameter calibration unit completes parameter assignment, and value calculation unit calculates the current comprehensive value and generates resource tags through spatiotemporal value quantification formula; encrypted resource index is uploaded to on-chain index storage unit, and resource details are stored in local detail storage unit. S3. Demand Release and Intelligent Matching: The target park releases its investment promotion needs. The demand parsing unit extracts the demand parameters and completes the initial screening. The industry distance calculation unit calculates the industry distance of each candidate resource. The matching degree ranking unit calculates the score through the matching degree formula and outputs the matching list in descending order. S4. Encrypted Resource Interaction and Integration: After the requester selects the target resource, it initiates a detailed access request. After the permission verification is passed, it obtains the decryption key, decrypts and views the resource details on the local node, and the two parties conduct offline integration. S5. Project Implementation and Profit Sharing Evidence Storage: After the project is implemented, the implementation verification unit cross-verifies the authenticity of the implementation information. Once the verification is passed, the profit sharing execution unit is triggered to complete the automatic transfer of income. The evidence storage unit will put the entire process data on the blockchain for evidence storage and update the dynamic credit score of the corresponding node in a synchronous manner.

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