Electronic official document circulation effectiveness evaluation method

Abstract

The invention discloses an electronic official document circulation efficiency evaluation method, which comprises the following steps: constructing a node-signal model, and obtaining electronic official document circulation data based on nodes in the node-signal model; obtaining a circulation efficiency multi-dimensional index based on the electronic official document circulation data; mapping the circulation efficiency multi-dimensional indexes to corresponding state levels according to a preset membership function, and obtaining a membership matrix of each index; calculating based on the objective weight of each index and the membership matrix to obtain a comprehensive evaluation result vector; and obtaining an electronic official document circulation efficiency level based on the comprehensive evaluation result vector. The invention provides a scientific, systematic and practical method for evaluating the electronic official document circulation efficiency, can effectively support optimization and decision of official document circulation management, and has remarkable application value and popularization significance.

Description

Technical Field

[0001] This invention belongs to the field of performance evaluation technology, and in particular relates to a method for evaluating the performance of electronic document circulation. Background Technology

[0002] With the development of information technology, electronic document systems have gradually replaced traditional paper-based document circulation, becoming an important means of improving administrative efficiency. However, in the current electronic document circulation process, due to differences in office conditions, business training levels, and cognitive abilities among various units, congestion and delays frequently occur at document processing nodes, severely restricting circulation efficiency. Current evaluation methods for electronic document effectiveness mostly rely on subjective experience or single indicators, lacking systematic, dynamic, and quantitative analysis capabilities, making it difficult to accurately reflect the real-time status and overall effectiveness of document circulation. For example, existing technologies fail to comprehensively and effectively integrate multi-dimensional parameters, leading to one-sided evaluation results; at the same time, traditional weighting methods are highly subjective and cannot objectively reflect the degree of influence of each indicator on overall effectiveness, limiting the scientific validity and applicability of evaluation models.

[0003] Furthermore, existing research lacks refined grading standards for the status of document circulation, making it difficult to accurately identify congestion levels at nodes and failing to provide a reliable basis for optimizing resource allocation. Some studies have attempted to draw on traffic flow models, but have not fully considered the special characteristics of document processing, such as differences in document types, resulting in insufficient adaptability of the models to actual business scenarios. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention proposes a method for evaluating the efficiency of electronic document circulation, thereby resolving the issues present in the prior art.

[0005] To achieve the above objectives, the present invention provides a method for evaluating the efficiency of electronic document circulation, comprising:

[0006] Construct a node-signal model, and obtain electronic document circulation data based on the nodes in the node-signal model;

[0007] Based on the aforementioned electronic document circulation data, multi-dimensional indicators of circulation efficiency are obtained;

[0008] The multidimensional indicators of circulation efficiency are mapped to the corresponding state levels according to the preset membership function to obtain the membership matrix of each indicator.

[0009] The comprehensive evaluation result vector is calculated based on the objective weights and membership matrices of each indicator.

[0010] The efficiency level of electronic document circulation is obtained based on the comprehensive evaluation result vector.

[0011] Optionally, the process of constructing the node-signal model includes: abstracting electronic document processing personnel as flow nodes, wherein the processing personnel include, but are not limited to, staff, assistants, clerks and secretaries; defining node states based on the traffic light mechanism, wherein the working state of a node corresponds to the green light pass state and the rest state corresponds to the red light stop state.

[0012] Optionally, the multi-dimensional indicators of workflow efficiency include average document processing speed, node saturation, and average document delay time.

[0013] Optionally, the average processing speed of the official documents is:

[0014]

[0015] In the formula, v represents the average document processing speed per unit time. q Let q be the processing time for the q-th document, where Q is the number of documents arriving per unit time.

[0016] The node saturation is:

[0017]

[0018] In the formula, S i Let Q be the saturation of the i-th node. i Let C be the number of documents arriving at the i-th node per unit time. i For node traffic capacity;

[0019] The average delay time for the official documents is:

[0020]

[0021] In the formula, C is the signal period. For green credit ratio, Q0 represents the saturation level and the average document balance.

[0022] Optionally, the status levels can be divided according to the numerical range of the multi-dimensional indicators of circulation efficiency, including smooth flow, basically smooth flow, light congestion, moderate congestion, and severe congestion.

[0023] Optionally, the preset membership function is a trapezoidal membership function.

[0024] Optionally, the process of obtaining the comprehensive evaluation result vector includes:

[0025] The multidimensional index data of circulation efficiency are normalized to obtain a normalized matrix; the information entropy of each index is calculated based on the normalized matrix; the degree of variation coefficient is obtained based on the information entropy; and the weight of the index is calculated based on the normalization result of the degree of variation coefficient.

[0026] The present invention also provides a computer device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the computer program to implement the steps of the above method.

[0027] The present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method.

[0028] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described method.

[0029] Compared with the prior art, the present invention has the following advantages and technical effects:

[0030] This invention effectively solves the problem of assessing congestion and delays in the electronic document circulation process by introducing a membership matrix and a combined weighting method, combined with the entropy weighting method to determine objective weights. The model uses key parameters such as average document processing speed, saturation, and average document delay time as indicators to classify document circulation status into five levels: smooth, basically smooth, slightly congested, moderately congested, and severely congested. This scientifically defines the efficiency of electronic document circulation, achieves quantitative assessment of electronic document circulation efficiency, reduces the subjective errors caused by traditional manual assessment methods, enriches the granularity of electronic document circulation efficiency assessment, improves the timeliness of electronic document efficiency assessment, and strongly supports the optimization and improvement of the electronic document circulation system. Attached Figure Description

[0031] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0032] Figure 1 This is a schematic diagram illustrating random delays in electronic documents according to an embodiment of the present invention;

[0033] Figure 2 This is a schematic diagram of the membership function of the average flow velocity of official documents in an embodiment of the present invention;

[0034] Figure 3 This is a schematic diagram of the document circulation saturation membership function according to an embodiment of the present invention;

[0035] Figure 4 This is a schematic diagram of the membership function of the average delay time of document circulation in an embodiment of the present invention;

[0036] Figure 5 This is a schematic diagram of a method according to an embodiment of the present invention. Detailed Implementation

[0037] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0038] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0039] Example 1

[0040] like Figure 1-5 As shown, this embodiment provides a method for evaluating the efficiency of electronic document circulation, including:

[0041] Construct a node-signal model, and obtain electronic document circulation data based on the nodes in the node-signal model;

[0042] Furthermore, the process of constructing the node-signal model includes: abstracting electronic document processing personnel as flow nodes, wherein the processing personnel include, but are not limited to, staff, assistants, clerks and secretaries; defining node states based on the traffic light mechanism, wherein the working state of a node corresponds to the green light pass state and the rest state corresponds to the red light stop state.

[0043] Specifically, considering the progress of electronic document pilot programs, this paper analyzes the current work status of document processing personnel at various levels and of various types during the electronic document circulation process. Based on relevant research on road traffic state assessment models, an innovative electronic document circulation efficiency assessment model is proposed. This model abstracts electronic document processing personnel in various units, including staff, assistants, clerks, and secretaries, as nodes in the electronic document circulation process, analogous to intersections in road traffic. Since document processing personnel have two states—working and resting—within a time period, similar to the concepts of green light (go) and red light (stop) in road traffic, the document circulation is modeled according to road traffic state assessment.

[0044] Based on the aforementioned electronic document circulation data, multi-dimensional indicators of circulation efficiency are obtained;

[0045] Furthermore, the multi-dimensional indicators of workflow efficiency include the average processing speed of official documents, node saturation, and average delay time of official documents.

[0046] Specifically, in the research on the efficiency evaluation model of electronic document circulation, the description of the status of document circulation at each node is somewhat ambiguous and difficult to quantify. Researching relevant indicators that can characterize the status of document circulation at each node helps to more accurately describe the smoothness or congestion of that node. Based on the principles of applicability, scientific rigor, systematicity, and dynamism in indicator selection, and comprehensively considering the current status of electronic document circulation operations, average document processing speed, saturation, and average document delay time are selected as model parameters. By constructing a document circulation model, a comprehensive evaluation of the document circulation status can be achieved.

[0047] Furthermore, the average processing speed of the official documents is:

[0048]

[0049] In the formula, v represents the average document processing speed per unit time. q Let q be the processing time for the q-th document, where Q is the number of documents arriving per unit time.

[0050] Specifically, during the electronic document circulation process, due to significant differences in the types and quantities of documents processed by various units and departments, the average processing speed—that is, the average processing time per unit of time—is used to describe the efficiency of electronic document circulation in order to intuitively demonstrate its operational status. A high processing speed indicates that documents flow quickly within the system, promptly meeting various needs and demonstrating relatively good processing capabilities.

[0051] The node saturation is:

[0052]

[0053] In the formula, S i Let Q be the saturation of the i-th node. i Let C be the number of documents arriving at the i-th node per unit time. i For node traffic capacity;

[0054] Specifically, saturation is the ratio of document flow to maximum flow capacity, which can be used to show the document load level of each flow node. A reasonable saturation means that the system can operate efficiently while maintaining appropriate flexibility and responsiveness, avoiding efficiency decline due to overload. When the saturation is close to 1, it indicates that node processing will gradually become congested, and even a slight increase in flow may cause the document flow situation to deteriorate, or even cause traffic jams.

[0055] The average delay time for the official documents is:

[0056]

[0057] In the formula, C is the signal period. For green credit ratio, Q0 represents the saturation level and the average document balance.

[0058] Specifically, the average delay time describes the delay situation in the document circulation process, reflecting the time wasted during document circulation. Lower delay times generally indicate smooth system operation and a rapid response to various needs. The delay time of documents flowing to each node is related to the number of documents in the queue, but mainly depends on the arrival rate, outflow rate, and the node's saturation capacity. Considering that the document circulation capacity of each node remains relatively stable in the short term, the following assumptions should be made before model construction:

[0059] The document processing cycle for each node is C;

[0060] The average arrival rate q of official documents is constant per unit time.

[0061] The average saturation S (the ratio of document flow v to saturation flow rate c) of the node is less than 1.

[0062] For document processing at a single node, assuming the node's entry capacity and document arrival rate remain stable, there is a linear relationship between document delay time and arrival rate. However, due to oversaturation in certain cycles or other reasons during the study period, there may still be documents remaining at each node when the green light ends. Let the average document "reserve" be Q0. Figure 1 The horizontal line represents the document delay time, and the vertical line represents the number of documents queued at different instants. Therefore, the total delay time of all documents within one signal cycle is:

[0063]

[0064] because Therefore, the solution is... then:

[0065]

[0066] Since the total number of incoming documents is qC, the average delay time of the documents is... The average delay time for official documents is:

[0067]

[0068] When there is a queue of documents Q0 waiting in the initial stage of the selected analysis period, if the initial queue length is 0, i.e., Q0 = 0, then there are no documents waiting to be processed at the time of the selected analysis period. In this case, the average document delay model is:

[0069]

[0070] Where C is the signal period. For green credit ratio, This represents saturation.

[0071] The multi-dimensional indicators of flow efficiency are mapped to the corresponding state levels according to the preset membership function to obtain the membership matrix of each indicator; the state levels are divided according to the numerical range of the multi-dimensional indicators of flow efficiency, and the state levels include smooth flow, basically smooth flow, light congestion, moderate congestion and severe congestion; the preset membership function adopts the trapezoidal membership function.

[0072] Specifically, the evaluation of document circulation status is somewhat subjective and ambiguous. By classifying the document circulation status, the operational status of document circulation can be qualitatively described. The classification of node status levels can be defined as a set of similar document circulation situations, but there is currently no unified standard for defining similarity domestically and internationally. Based on previous experience in classifying document circulation status levels and the current needs of traffic management, this paper classifies node document circulation status into five levels: smooth flow, basically smooth flow, light congestion, moderate congestion, and severe congestion.

[0073] By selecting three document circulation indicators—average circulation speed, document circulation saturation, and average document circulation delay—the status of document circulation at each node can be reflected. However, there is ambiguity in the correspondence between these indicators and the various statuses of document circulation. Therefore, using indicator ranges to correspond to document circulation statuses is more in line with reality. As shown in Table 1, the value ranges of each circulation indicator under the five document circulation statuses are set.

[0074] Table 1

[0075]

[0076] Note: v f Here, represents the free-flow velocity, and represents the average flow velocity of documents under low flow conditions. They are respectively The maximum and minimum values, s max This represents the maximum value of saturation. This represents the maximum average delay for official documents.

[0077] Based on the range given in the table, the circulation status of each document is described as follows from three dimensions: average document processing speed, saturation level, and average document delay time:

[0078] (I) Unobstructed Status

[0079] Documents arriving at the node are processed quickly, and staff can freely choose the processing speed; document circulation density is low, and document volume is very small; there is almost no queuing or waiting during document circulation.

[0080] (II) Basically unobstructed

[0081] Documents arriving at the nodes can generally flow smoothly at the expected speed; the document flow rate along the circulation path has increased; documents can generally pass through smoothly with few queuing or waiting situations.

[0082] (III) Mild congestion

[0083] The document flow rate to the node decreases, making it difficult for document processing personnel to easily handle document processing work; the document traffic at the node increases, and the processing channel becomes congested; documents need to queue and wait to pass through the node, but the waiting time is still acceptable.

[0084] (iv) Moderate congestion

[0085] The processing speed of documents arriving at a node is limited, and they can only move with the previous document; the number of documents is large, and the node is close to saturation; the waiting time for processing documents becomes longer.

[0086] (v) Severe congestion

[0087] The document processing speed of the node is very low, making it difficult to pass through normally; the document processing density is very high, and the node is oversaturated; documents have difficulty passing through and all need to wait in queues, with long queuing times.

[0088] Considering the complex correlation between various indicators and document circulation status, the evaluation model employs a comprehensive evaluation method to establish connections between indicators and status levels at each level. Specifically, it obtains the membership degree between each indicator and circulation status level through membership functions, and then combines the membership evaluation results of each indicator using a comprehensive document circulation evaluation model to obtain the comprehensive evaluation result of document circulation status. Based on the value range of indicators at each level, a single-indicator membership function is established, and the commonly used trapezoidal membership function is selected to calculate the membership degree of each indicator. The interval value under a certain level is mapped to 1, and the membership degree of indicator values ​​in adjacent intervals linearly decreases to 0.

[0089] The membership functions for the average document processing speed corresponding to the circulation status of smooth, basically smooth, slightly congested, moderately congested, and severely congested are denoted as V1, V2, V3, V4, and V5, respectively, as follows:

[0090]

[0091] The saturation levels correspond to the membership functions S1, S2, S3, S4, and S5 for traffic conditions of smooth flow, mostly smooth flow, light congestion, moderate congestion, and severe congestion, respectively, as detailed below:

[0092]

[0093] The membership functions for the average document delay time corresponding to traffic conditions of smooth flow, basically smooth flow, light congestion, moderate congestion, and severe congestion are denoted as D1, D2, D3, D4, and D5, respectively, as follows:

[0094]

[0095] The membership function graphs of the three indicators—average flow velocity V, document flow saturation S, and average document flow delay D—at the corresponding document flow status levels are shown below. Figure 2-4 As shown.

[0096] The comprehensive evaluation result vector is calculated based on the objective weights and membership matrices of each indicator.

[0097] The efficiency level of electronic document circulation is obtained based on the comprehensive evaluation result vector.

[0098] Furthermore, the process of obtaining the comprehensive evaluation result vector includes:

[0099] The multidimensional index data of circulation efficiency are normalized to obtain a normalized matrix; the information entropy of each index is calculated based on the normalized matrix; the degree of variation coefficient is obtained based on the information entropy; and the weight of the index is calculated based on the normalization result of the degree of variation coefficient.

[0100] The comprehensive evaluation of document circulation status can fully demonstrate the overall operational status of document circulation. The following are the steps for the comprehensive evaluation of document circulation status:

[0101] Step 1: Determine the comprehensive evaluation index system. Let the evaluation index set consisting of m evaluation indicators be D = (d1, d2…d…). m ).

[0102] Step 2: Determine the comment set. Let the comment set consisting of h evaluation levels be l = (l1, l2, ..., ln). h ).

[0103] Step 3: Determine the set of evaluation objects. Let the set of evaluation objects consisting of n evaluation objects be X = (X1, X2, ..., Xn). n ).

[0104] Step 4: Calculate the relative membership matrix. Establish the membership matrix for each individual evaluation object X. i =(X i1 ,X i2 …X im The relative membership matrix R) i :

[0105]

[0106] Where, r ijk To evaluate element Xij In the evaluation comments k The membership degree on the table is i = 1, 2, ..., n; j = 1, 2, ..., m; k = 1, 2, ..., h.

[0107] Step 5: Determine the indicator weights. Let the weight vector of the m evaluation indicators be W = (w1, w2, ... w...). m )′.

[0108] Step 6: Calculate the evaluation result matrix. First, calculate the comprehensive evaluation result vector B for each evaluation object. i Then, construct the evaluation result matrix B = (B1, B2, ..., B) for the evaluation object set X. n ),B i The calculation formula is as follows:

[0109] B i =(b i1 b i2 b i3 , ...b ih )′=R i W;

[0110] Step 5, determining the indicator weights, includes: objective weight calculation based on the entropy weight method. The entropy weight method calculates weights using the information entropy of each indicator's data value, and then uses the entropy weight to correct the weight vector, resulting in more accurate weights.

[0111] Step 1: Normalize the raw data. To eliminate the influence of the dimensions of each indicator on the calculation results, normalize the original evaluation object set X = (x ij ) n×m Normalization is performed. Specifically, the positive evaluation index values ​​are forward standardized. Inverse evaluation index value reverse standardization in, For indicator d j The maximum value of all evaluated objects. For indicator d j The minimum value of all evaluated objects. From this, we obtain the normalized matrix Y = (y ij ) n×m .

[0112] Step 2: Calculate index d j Information entropy h j .in In the formula, f represents the feature weight of the i-th evaluation object under the j-th indicator. In particular, f ij When = 0, f in the formula ij lnf ij =0.

[0113] Step 3: Calculate index d j The coefficient of variation b j This is also called information redundancy. The calculation formula is as follows:

[0114] b j =1-h j ;

[0115] Step 4: Calculate the entropy weight w of the index based on the normalized result of the coefficient of variation. j .

[0116]

[0117] The present invention also provides a computer device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the computer program to implement the steps of the above method.

[0118] The present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method.

[0119] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described method.

[0120] The above are merely preferred embodiments of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A method for evaluating the efficiency of electronic document circulation, characterized in that, Includes the following steps: Construct a node-signal model, and obtain electronic document circulation data based on the nodes in the node-signal model; Based on the aforementioned electronic document circulation data, multi-dimensional indicators of circulation efficiency are obtained; The multidimensional indicators of circulation efficiency are mapped to the corresponding state levels according to the preset membership function to obtain the membership matrix of each indicator. The comprehensive evaluation result vector is calculated based on the objective weights and membership matrices of each indicator. The efficiency level of electronic document circulation is obtained based on the comprehensive evaluation result vector.

2. The method for evaluating the efficiency of electronic document circulation according to claim 1, characterized in that, The process of constructing the node-signal model includes: abstracting electronic document processing personnel as flow nodes, including but not limited to staff, assistants, clerks and secretaries; defining node states based on traffic light mechanisms, wherein the working state of a node corresponds to the green light pass state and the rest state corresponds to the red light stop state.

3. The method for evaluating the efficiency of electronic document circulation according to claim 1, characterized in that, The multi-dimensional indicators of workflow efficiency include average document processing speed, node saturation, and average document delay time.

4. The method for evaluating the efficiency of electronic document circulation according to claim 3, characterized in that, The average processing speed of the official documents is: In the formula, v represents the average document processing speed per unit time. q Let q be the processing time for the q-th document, where Q is the number of documents arriving per unit time. The node saturation is: In the formula, S i Let Q be the saturation of the i-th node. i Let C be the number of documents arriving at the i-th node per unit time. i For node traffic capacity; The average delay time for the official documents is: In the formula, C is the signal period. For green credit ratio, Q0 represents the saturation level and the average document balance.

5. The method for evaluating the efficiency of electronic document circulation according to claim 1, characterized in that, The status levels are divided according to the numerical range of the multi-dimensional indicators of circulation efficiency, including smooth flow, basically smooth flow, light congestion, moderate congestion, and severe congestion.

6. The method for evaluating the efficiency of electronic document circulation according to claim 1, characterized in that, The preset membership function adopts a trapezoidal membership function.

7. The method for evaluating the efficiency of electronic document circulation according to claim 1, characterized in that, The process of obtaining the comprehensive evaluation result vector includes: The multidimensional index data of circulation efficiency are normalized to obtain a normalized matrix; the information entropy of each index is calculated based on the normalized matrix; the degree of variation coefficient is obtained based on the information entropy; and the weight of the index is calculated based on the normalization result of the degree of variation coefficient.

8. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the steps of the method according to any one of claims 1-7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the method described in any one of claims 1-7.

10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the steps of the method described in any one of claims 1-7.

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