Enterprise competition management method and system based on bidding and tendering big data

Abstract

The invention belongs to the field of bidding and tendering, relates to a data analysis technology, is used for solving the problem that various requirements of enterprise users cannot be met due to the fact that bidding project recommendation is provided for the enterprise users according to a single standard or basis in the prior art, and particularly relates to an enterprise competition management method and system based on bidding and tendering big data. The enterprise management platform is in communication connection with a document screening module, a user analysis module, a recommendation output module and a bidding database; the document screening module is used for performing preliminary screening analysis on the bid invitation documents: marking enterprise users performing bid invitation analysis as analysis objects, and extracting preliminary screening items from the bid invitation database through the analysis objects; according to different target tendency and operation tendency combinations selected by the enterprise user, secondary screening is carried out on the primarily screened items, the matching degree of the recommended items obtained through secondary screening and the requirements of the enterprise user is high, and therefore the auditing efficiency of the enterprise user and the selection probability of the recommendation result are improved.

Description

Technical Field

[0001] The present invention belongs to the field of bidding and tendering, and relates to data analysis technology, and specifically to an enterprise competition management method and system based on bidding and tendering big data. Background Art

[0002] Bidding is a form of comprehensive economic responsibility system to promote competition in the field of infrastructure construction. Generally, several construction units participate in the bidding for the project, and the bidding unit selects the best ones. Whoever has the shortest construction period, low cost, high quality and good reputation will be awarded the project task. The contractor and the contracting unit will sign a contract and the construction will be organized in a turnkey manner from beginning to end.

[0003] The enterprise competition management method in the prior art can only provide bidding project recommendations for enterprise users based on a single standard or basis. However, with the development of society, the needs of enterprise users in bidding selection are diverse, and the bidding project recommendation results of a single standard cannot meet the bidding selection needs of all users.

[0004] In view of the above technical problems, this application proposes a solution. Summary of the invention

[0005] The purpose of the present invention is to provide a method and system for enterprise competition management based on bidding big data, which is used to solve the problem that the existing technology provides bidding project recommendations for enterprise users with a single standard or basis, and cannot meet the diverse needs of enterprise users;

[0006] The technical problem to be solved by the present invention is: how to provide an enterprise competition management method and system based on bidding big data that can adopt different standards to recommend bidding projects for enterprise users.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] An enterprise competition management system based on bidding big data, comprising an enterprise management platform, wherein the enterprise management platform is communicatively connected with a document screening module, a user analysis module, a recommendation output module and a bidding database;

[0009] The document screening module is used to perform preliminary screening analysis on the bidding documents in the bidding database: marking the enterprise users who perform bidding analysis as analysis objects, extracting preliminary screening items from the bidding database through the analysis objects, and sending all preliminary screening items to the recommendation output module through the enterprise management platform;

[0010] The user analysis module is used to analyze user needs and generate secondary screening needs, and send the secondary screening needs to the recommendation output module through the enterprise management platform;

[0011] The recommendation output module is used to perform secondary screening analysis on the primary screening items according to the secondary screening requirements and obtain recommended items, and send all recommended items to the corresponding enterprise user mobile phone terminals through the enterprise management platform.

[0012] Furthermore, the extraction process of the preliminary screening projects includes: retrieving the region of business address and business scope in the business license of the analysis object, marking the bidding documents in the bidding status in the bidding database as public projects, and marking the public data corresponding to the service area and service type and the region of business address and business scope of the analysis object as preliminary screening projects.

[0013] Furthermore, the generation process of secondary screening needs includes: the analysis object selects target tendencies and operation tendencies through the user analysis module, the target tendencies include value priority, probability priority, impact priority and comprehensive priority, and the operation tendencies include service concentration and service dispersion; the target tendencies and operation tendencies selected by the analysis object constitute the secondary screening needs.

[0014] Furthermore, the specific process of the recommended output module performing secondary screening analysis on the primary screening items according to the secondary screening requirements includes:

[0015] The primary screening items are prioritized according to the target tendency of the analysis object selection to obtain the basic sequence;

[0016] The basic sequence is intercepted and processed according to the operation tendency selected by the analysis object to obtain the recommended items.

[0017] Furthermore, the basic sequence acquisition process includes:

[0018] When the target tendency of the analysis object selection is value priority: extract the bidding requirements from the preliminary screening projects, then extract the completed bidding projects from the bidding database, mark the completed bidding projects with the highest similarity between the bidding requirements and the bidding requirements of the preliminary screening projects as value reference projects, mark the overall revenue and overall cost values ​​of the winning enterprises of the value reference projects after completing the bidding projects as the revenue data and cost data of the preliminary screening projects, mark the ratio of the revenue data to the cost data as the value data JZ of the preliminary screening projects, and arrange all the preliminary screening projects in descending order according to the value data JZ to obtain the basic sequence;

[0019] When the target tendency of selecting the analysis object is probability priority: obtain the service type corresponding to the business scope of the analysis object in the preliminary screening project and mark it as the bidding type, mark all enterprises whose business scope includes the bidding type in the area where the business address of the analysis object is located as bidding objects, calculate the volume coefficient TL of all bidding objects, arrange the analysis object and the bidding object in descending order according to the volume coefficient TL to obtain a bidding sequence, mark the ratio of the maximum sequence number of the bidding sequence to the sequence number of the analysis object in the bidding sequence as the probability data GL of the preliminary screening project, and arrange all the preliminary screening projects in descending order according to the probability data GL to obtain a basic sequence;

[0020] When the target tendency of selecting the analysis object is to prioritize impact: calculate the volume coefficient TL of the bidding enterprises corresponding to all the preliminary screening projects, mark the ratio of the volume coefficient TL of the bidding enterprise to the volume coefficient TL of the analysis object as the impact data YX of the preliminary screening project, and arrange the preliminary screening projects in descending order according to the value of the impact data YX to obtain the basic sequence.

[0021] Furthermore, the basic sequence acquisition process also includes:

[0022] When the target tendency of the analysis object selection is comprehensive priority: through the formula The comprehensive coefficient ZH of the analysis object relative to the initial screening item is obtained, where k1, k2 and k3 are all proportional coefficients, and k1>k2>k3>1; the initial screening items are arranged in descending order according to the value of the comprehensive coefficient ZH to obtain the basic sequence.

[0023] Furthermore, the process of obtaining recommended items includes:

[0024] When the operation tendency of the analysis object selection is service dispersion: the top L1 preliminary screening items are intercepted from the basic sequence as recommended items;

[0025] When the operation tendency selected for the analysis object is service concentration: the value data JZ, probability data GL, impact data YX or comprehensive coefficient ZH of the preliminary screening items are marked as the target performance values ​​of the preliminary screening items, the average of the target performance values ​​of all preliminary screening items corresponding to the target tendency of the same bidding type is calculated and marked as the concentration coefficient of the bidding type, the bidding type with the largest concentration coefficient is marked as the concentrated type, the preliminary screening items containing the concentrated type are sorted according to the target performance values ​​of the corresponding target tendencies to obtain a concentrated sequence, and the top L1 preliminary screening projects in the concentrated sequence are intercepted as recommended projects.

[0026] A method for enterprise competition management based on bidding big data, comprising the following steps:

[0027] Step 1: Perform preliminary screening analysis on the bidding documents in the bidding database: mark the enterprise users who conduct bidding analysis as the analysis object, and extract the preliminary screening items in the bidding database based on the business address area and business scope in the business license of the analysis object;

[0028] Step 2: Analyze user needs: The analysis object selects the target tendency and operation tendency through the user analysis module, and the target tendency and operation tendency selected by the analysis object constitute the secondary screening needs;

[0029] Step 3: Prioritize the initial screening items according to the target tendency selected by the analysis object to obtain the basic sequence;

[0030] Step 4: According to the operation tendency selected by the analysis object, the basic sequence is intercepted and processed to obtain the recommended items.

[0031] The present invention has the following beneficial effects:

[0032] 1. The document screening module can be used to conduct preliminary screening and analysis of the bidding documents in the bidding database, and screen the bidding documents in the bidding state according to the business scope and region of the enterprise user, so as to improve the matching degree between the preliminary screening project and the enterprise user, and provide data support for the secondary screening analysis process;

[0033] 2. The user analysis module can be used to analyze user needs. The target tendency and operation tendency reflect the purpose and execution inertia of the enterprise user in the bidding execution process. For example, when the target tendency selects influence priority, it means that the enterprise user's bidding purpose is to increase visibility and expand influence. When the operation tendency selects service concentration, bidding for multiple projects can reduce the pressure of preparing bidding documents. Through the combination of target tendency and operation tendency;

[0034] 3. The recommendation output module can be used to conduct a secondary screening analysis on the initial screening items according to the secondary screening needs. The initial screening items can be secondary screened according to the different target tendencies and operation tendency combinations selected by the enterprise users. The recommended items obtained from the secondary screening have a high degree of match with the needs of the enterprise users, thereby improving the review efficiency of the enterprise users and the probability of selecting the recommended results. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] 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 only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0036] Figure 1 is a system block diagram of Embodiment 1 of the present invention;

[0037] Figure 2 This is a flow chart of the method of Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0038] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than 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 are within the scope of protection of the present invention.

[0039] Embodiment 1

[0040] like Figure 1 As shown, an enterprise competition management system based on bidding big data includes an enterprise management platform, which is communicatively connected to a document screening module, a user analysis module, a recommendation output module and a bidding database.

[0041] The document screening module is used to perform preliminary screening analysis on the bidding documents in the bidding database: mark the corporate users who conduct the bidding analysis as analysis objects, retrieve the region and business scope of the business address in the business license of the analysis object, mark the bidding documents in the bidding status in the bidding database as public projects, mark the public data corresponding to the service area and service type and the region and business scope of the business address of the analysis object as preliminary screening projects, and send all preliminary screening projects to the recommendation output module through the enterprise management platform; screen the bidding documents in the bidding status according to the business scope and region of the corporate users, so as to improve the matching degree between the preliminary screening projects and the corporate users, and provide data support for the secondary screening analysis process.

[0042] The user analysis module is used to analyze user needs: the analysis object selects target tendency and operation tendency through the user analysis module. The target tendency includes value priority, probability priority, impact priority and comprehensive priority, and the operation tendency includes service concentration and service dispersion; the target tendency and operation tendency selected by the analysis object constitute the secondary screening demand, and the secondary screening demand is sent to the recommendation output module through the enterprise management platform; the target tendency and operation tendency reflect the purpose and execution inertia of the enterprise user in the process of this bidding execution. For example, when the target tendency selects impact priority, it means that the purpose of the enterprise user's bidding is to increase its popularity and expand its influence. When the operation tendency selects service concentration, bidding for multiple projects can reduce the pressure of preparing bidding documents through the combination of target tendency and operation tendency.

[0043] The recommended output module is used to conduct secondary screening analysis on the primary screening items according to the secondary screening requirements: the primary screening items are prioritized according to the target tendency selected by the analysis object to obtain the basic sequence;

[0044] When the target tendency of the analysis object selection is value priority: extract the bidding requirements from the preliminary screening projects, then extract the completed bidding projects from the bidding database, mark the completed bidding projects with the highest similarity between the bidding requirements and the bidding requirements of the preliminary screening projects as value reference projects, mark the overall revenue and overall cost values ​​of the winning enterprises of the value reference projects after completing the bidding projects as the revenue data and cost data of the preliminary screening projects, mark the ratio of the revenue data to the cost data as the value data JZ of the preliminary screening projects, and arrange all the preliminary screening projects in descending order according to the value data JZ to obtain the basic sequence;

[0045] When the target tendency of selecting the analysis object is probability priority: obtain the service type corresponding to the business scope of the analysis object in the preliminary screening project and mark it as the bidding type, mark all enterprises whose business scope includes the bidding type in the area where the business address of the analysis object is located as bidding objects, calculate the volume coefficient TL of all bidding objects, arrange the analysis object and the bidding object in descending order according to the volume coefficient TL to obtain a bidding sequence, mark the ratio of the maximum sequence number of the bidding sequence to the sequence number of the analysis object in the bidding sequence as the probability data GL of the preliminary screening project, and arrange all the preliminary screening projects in descending order according to the probability data GL to obtain a basic sequence;

[0046] When the target tendency of selecting the analysis object is to prioritize influence: calculate the volume coefficient TL of the bidding enterprises corresponding to all the preliminary screening projects, mark the ratio of the volume coefficient TL of the bidding enterprise to the volume coefficient TL of the analysis object as the influence data YX of the preliminary screening project, and arrange the preliminary screening projects in descending order of the influence data YX to obtain the basic sequence; it should be noted that the volume coefficient TL is a value that reflects the overall strength of the bidding enterprise. The larger the value of the volume coefficient TL, the stronger the overall strength of the bidding enterprise. The volume coefficient TL can be calculated by taking the weighted sum of parameters such as the registered capital of the bidding enterprise, the number of registered employees, and the area occupied by the office.

[0047] When the target tendency of the analysis object selection is comprehensive priority: through the formula The comprehensive coefficient ZH of the analysis object relative to the initial screening item is obtained, where k1, k2 and k3 are all proportional coefficients, and k1>k2>k3>1; the initial screening items are arranged in descending order according to the value of the comprehensive coefficient ZH to obtain a basic sequence;

[0048] According to the operation tendency of the analysis object selection, the basic sequence is intercepted to obtain the recommended items;

[0049] When the operation tendency of the analysis object selection is service dispersion: the top L1 preliminary screening items are intercepted from the basic sequence as recommended items. L1 is a numerical constant. The specific value of L1 is set by the management personnel.

[0050] When the operation tendency selected for the analysis object is service concentration: the value data JZ, probability data GL, impact data YX or comprehensive coefficient ZH of the preliminary screening project are marked as the target performance value of the preliminary screening project, the average target performance value of the target tendency of all preliminary screening projects of the same bidding type is calculated and marked as the concentration coefficient of the bidding type, the bidding type with the largest concentration coefficient is marked as the concentrated type, the preliminary screening projects containing the concentrated type are sorted according to the target performance values ​​of the corresponding target tendency to obtain a concentrated sequence, and the top L1 preliminary screening projects are intercepted from the concentrated sequence as recommended projects;

[0051] All recommended items are sent to the corresponding enterprise users' mobile terminals through the enterprise management platform; the initial screening items are screened for the second time according to the different target tendencies and operation tendency combinations selected by the enterprise users. The recommended items obtained from the secondary screening have a high degree of match with the needs of the enterprise users, thereby improving the review efficiency of the enterprise users and the probability of selection of the recommended results.

[0052] Embodiment 2

[0053] like Figure 2 As shown, a method for enterprise competition management based on bidding big data includes the following steps:

[0054] Step 1: Perform preliminary screening analysis on the bidding documents in the bidding database: mark the enterprise users who conduct bidding analysis as the analysis object, and extract the preliminary screening items in the bidding database based on the business address area and business scope in the business license of the analysis object;

[0055] Step 2: Analyze user needs: The analysis object selects the target tendency and operation tendency through the user analysis module, and the target tendency and operation tendency selected by the analysis object constitute the secondary screening needs;

[0056] Step 3: Prioritize the initial screening items according to the target tendency selected by the analysis object to obtain the basic sequence;

[0057] Step 4: According to the operation tendency selected by the analysis object, the basic sequence is intercepted and processed to obtain the recommended items.

[0058] A corporate competition management method and system based on bidding big data. When working, the corporate users who conduct bidding analysis are marked as analysis objects, and the area and business scope of the business address in the business license of the analysis object are used to extract the initial screening items in the bidding database; the analysis object selects the target tendency and operation tendency through the user analysis module, and the target tendency and operation tendency selected by the analysis object constitute the secondary screening demand; the initial screening items are prioritized according to the target tendency selected by the analysis object to obtain a basic sequence; the basic sequence is intercepted and processed according to the operation tendency selected by the analysis object to obtain recommended items.

[0059] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

[0060] The above formulas are obtained by collecting a large amount of data and performing software simulation to select a formula close to the actual value. The coefficients in the formula are set by technicians in this field according to actual conditions; for example: Formula A technician in this field collects multiple groups of sample data and sets a corresponding comprehensive coefficient for each group of sample data; substitutes the set comprehensive coefficient and the collected sample data into the formula, and any three formulas constitute a three-variable linear equation system. The calculated coefficients are screened and averaged, and the values ​​of k1, k2 and k3 are obtained to be 3.68, 2.14 and 2.07 respectively;

[0061] The size of the coefficient is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the coefficient depends on the amount of sample data and the preliminary setting of the corresponding comprehensive coefficient for each group of sample data by technical personnel in this field; as long as it does not affect the proportional relationship between the parameter and the quantified value, such as the comprehensive coefficient is proportional to the value of the value data.

[0062] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0063] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. An enterprise competition management system based on bidding big data, characterized in that: It includes an enterprise management platform, which is communicatively connected to a document screening module, a user analysis module, a recommendation output module and a bidding database; The document screening module is used to perform preliminary screening analysis on the bidding documents in the bidding database: marking the enterprise users who perform bidding analysis as analysis objects, extracting preliminary screening items from the bidding database through the analysis objects, and sending all preliminary screening items to the recommendation output module through the enterprise management platform; The user analysis module is used to analyze user needs and generate secondary screening needs, and send the secondary screening needs to the recommendation output module through the enterprise management platform; The recommendation output module is used to perform secondary screening analysis on the primary screening items according to the secondary screening requirements and obtain recommended items, and send all recommended items to the corresponding enterprise user mobile phone terminals through the enterprise management platform.

2. According to claim 1, the enterprise competition management system based on bidding big data is characterized in that: The extraction process of the preliminary screening projects includes: retrieving the region and business scope of the business address in the business license of the analysis object, marking the bidding documents in the bidding status in the bidding database as public projects, and marking the public data corresponding to the service area and service type and the region and business scope of the business address of the analysis object as preliminary screening projects.

3. According to claim 2, the enterprise competition management system based on bidding big data is characterized in that: The generation process of secondary screening needs includes: the analysis object selects the target tendency and operation tendency through the user analysis module, the target tendency includes value priority, probability priority, impact priority and comprehensive priority, and the operation tendency includes service concentration and service dispersion; the target tendency and operation tendency selected by the analysis object constitute the secondary screening needs.

4. According to claim 3, the enterprise competition management system based on bidding big data is characterized in that: The specific process of the recommended output module to conduct secondary screening analysis on the primary screening items according to the secondary screening requirements includes: The primary screening items are prioritized according to the target tendency of the analysis object selection to obtain the basic sequence; The basic sequence is intercepted and processed according to the operation tendency selected by the analysis object to obtain the recommended items.

5. According to claim 4, the enterprise competition management system based on bidding big data is characterized in that: The process of obtaining the basic sequence includes: When the target tendency of the analysis object selection is value priority: extract the bidding requirements from the preliminary screening projects, then extract the completed bidding projects from the bidding database, mark the completed bidding projects with the highest similarity between the bidding requirements and the bidding requirements of the preliminary screening projects as value reference projects, mark the overall revenue and overall cost values ​​of the winning enterprises of the value reference projects after completing the bidding projects as the revenue data and cost data of the preliminary screening projects, mark the ratio of the revenue data to the cost data as the value data JZ of the preliminary screening projects, and arrange all the preliminary screening projects in descending order according to the value data JZ to obtain the basic sequence; When the target tendency of selecting the analysis object is probability priority: obtain the service type corresponding to the business scope of the analysis object in the preliminary screening project and mark it as the bidding type, mark all enterprises whose business scope includes the bidding type in the area where the business address of the analysis object is located as bidding objects, calculate the volume coefficient TL of all bidding objects, arrange the analysis object and the bidding object in descending order according to the volume coefficient TL to obtain a bidding sequence, mark the ratio of the maximum sequence number of the bidding sequence to the sequence number of the analysis object in the bidding sequence as the probability data GL of the preliminary screening project, and arrange all the preliminary screening projects in descending order according to the probability data GL to obtain a basic sequence; When the target tendency of selecting the analysis object is to prioritize impact: calculate the volume coefficient TL of the bidding enterprises corresponding to all the preliminary screening projects, mark the ratio of the volume coefficient TL of the bidding enterprise to the volume coefficient TL of the analysis object as the impact data YX of the preliminary screening project, and arrange the preliminary screening projects in descending order according to the value of the impact data YX to obtain the basic sequence.

6. The enterprise competition management system based on bidding big data according to claim 5 is characterized in that: The process of obtaining the basic sequence also includes: When the target tendency of the analysis object selection is comprehensive priority: through the formula The comprehensive coefficient ZH of the analysis object relative to the initial screening item is obtained, where k1, k2 and k3 are all proportional coefficients, and k1>k2>k3>1; the initial screening items are arranged in descending order according to the value of the comprehensive coefficient ZH to obtain the basic sequence.

7. The enterprise competition management system based on bidding big data according to claim 6 is characterized in that: The process of obtaining recommended items includes: When the operation tendency of the analysis object selection is service dispersion: the top L1 preliminary screening items are intercepted from the basic sequence as recommended items; When the operation tendency selected for the analysis object is service concentration: the value data JZ, probability data GL, impact data YX or comprehensive coefficient ZH of the preliminary screening items are marked as the target performance values ​​of the preliminary screening items, the average of the target performance values ​​of all preliminary screening items corresponding to the target tendency of the same bidding type is calculated and marked as the concentration coefficient of the bidding type, the bidding type with the largest concentration coefficient is marked as the concentrated type, the preliminary screening items containing the concentrated type are sorted according to the target performance values ​​of the corresponding target tendencies to obtain a concentrated sequence, and the top L1 preliminary screening projects in the concentrated sequence are intercepted as recommended projects.

8. A method for enterprise competition management based on bidding big data, characterized in that: The following steps are involved: Step 1: Perform preliminary screening analysis on the bidding documents in the bidding database: mark the enterprise users who conduct bidding analysis as the analysis object, and extract the preliminary screening items in the bidding database based on the business address area and business scope in the business license of the analysis object; Step 2: Analyze user needs: The analysis object selects the target tendency and operation tendency through the user analysis module, and the target tendency and operation tendency selected by the analysis object constitute the secondary screening needs; Step 3: Prioritize the initial screening items according to the target tendency selected by the analysis object to obtain the basic sequence; Step 4: According to the operation tendency selected by the analysis object, the basic sequence is intercepted and processed to obtain the recommended items.

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