Logistics service management system and method

Abstract

The invention provides a logistics service management system and method, and belongs to the technical field of logistics management, and the method specifically comprises the steps: carrying out the determination of reservation management and control conference rooms in different dates based on coincident data, based on the use data of conference rooms of different portrait stabilization types and departments, and a management and control processing method, and carrying out the management and control of the conference rooms; according to the management and control processing data and the use data of the conference room in different dates, when it is determined that the management and control optimization target in the conference room needs to be recognized, the requirement matching degree of the conference room in different departments is determined, and the requirement matching condition of the different departments and the conference room which cannot serve as the management and control optimization target is combined. And the recognition processing method taking the conference room as the control optimization target is determined, so that the use satisfaction of the conference rooms of different departments is improved.

Description

Technical Field

[0001] This invention belongs to the field of logistics management technology, and in particular relates to a logistics service management system and method. Background Technology

[0002] Meeting rooms are shared resources used by multiple departments, and existing reservation methods often rely on a first-come, first-served or random lottery system. Specifically, in invention patent application CN202411913542.8, "A Management Method, System, Storage Medium, and Electronic Device for Intelligent Meeting Rooms," a meeting room reservation request is obtained, and a reservation result is determined based on the reservation request and the latest status of each meeting room; the reservation result is then sent to the smart terminals of each participant. Implementing the technical solution provided in this application improves the efficiency of meeting room utilization; however, the above technical solution has the following technical problems: Existing technical solutions neglect to determine the management methods for meeting rooms based on the meeting needs of different departments and the degree to which those needs are met. In other words, they fail to dynamically determine how to manage meeting rooms, making it difficult to meet the meeting room usage needs of different departments and ensure the satisfaction of all departments in using the meeting rooms.

[0003] Therefore, there is an urgent need for a logistics service management system and methodology. Summary of the Invention

[0004] To achieve the objectives of this invention, the following technical solution is adopted: Specifically, this application provides a logistics service management method, which includes: S1 determines the availability of meeting rooms on different dates based on meeting room booking data, and determines the management and control method for the meeting rooms by combining the matching of available meeting rooms with the meeting needs of different departments. S2 determines the profile stability type of the department's meeting needs based on the department's meeting booking data. Based on different profile stability types, the department's meeting room usage data and management and control methods, the booking and management of meeting rooms on different dates is determined. When it is determined that the management and control optimization targets in the meeting rooms need to be identified and processed based on the management and control data and usage data of the meeting rooms on different dates, the process proceeds to the next step. S3 determines the degree of matching of the meeting room's needs with different departments, and, in combination with the demand matching of different departments with meeting rooms that cannot be used as management optimization targets, determines the identification and processing method for the meeting room as a management optimization target.

[0005] The beneficial effects of this invention are as follows: Based on different profile stability types, departmental meeting room usage data, and control methods, the determination of reserved and controlled meeting rooms for different dates is carried out. The core logic is to "minimize the impact on departments that have not recently met their meeting room usage needs." The method dynamically selects control meeting rooms. First, it identifies departments with low recent usage (departments with usage deviations, i.e., departments that cannot effectively meet their needs) and identifies their historical preferred meeting rooms. It systematically excludes or avoids selecting these "historically preferred meeting rooms that have not recently met their needs" as control targets, thereby ensuring that control measures mainly apply to meeting rooms with a weak correlation to the historical lack of recent effective demand meeting, achieving a balance between control efficiency and operational stability.

[0006] This method determines the identification and processing methods for meeting rooms as management optimization targets by considering the degree of demand matching between different departments and the demand matching between different departments and meeting rooms that cannot be used as management optimization targets. By analyzing the competitive environment types of the departments associated with the meeting room, the method for identifying the management optimization target that should be adopted for intelligent decision-making for each meeting room under management. This method aims to identify whether removing management control from a meeting room transforms it from a low-competition environment (because management restricts competitors) to a high-competition environment, and the actual impact of this transformation varies systematically across different departments. Through quantitative assessment of these impact differences, the system can accurately guide meeting rooms to different identification paths, ensuring that optimization decisions both release management redundancy and do not cause a sharp decline in the availability of specific departments.

[0007] Furthermore, the meeting room booking data is determined based on meeting rooms booked on different dates.

[0008] Furthermore, the availability of the meeting room is determined based on the dates on which the meeting room is not booked.

[0009] Furthermore, the method for determining the control and management method of the conference room is as follows: Determine the number of available meeting rooms on different dates based on the availability of meeting rooms on different dates; Based on the matching situation of available meeting rooms with the meeting needs of different departments, the matching departments for the available meeting rooms are determined; Based on the number of available meeting rooms on different dates and the matching departments of the available meeting rooms, the management and control methods for the meeting rooms are determined.

[0010] Furthermore, the method for determining the reserved and controlled meeting room is as follows: Using different profile stability types, the number of times the meeting room is used in the department within the most recent preset time period is determined from the meeting room usage data of the department, and the departments with usage deviations are determined based on the number of times they are used. Based on the degree of matching between the meeting room and the usage needs of the department with usage deviation, it is determined that the meeting room belongs to the department with usage deviation and matching meeting room usage. Based on the fact that the meeting room belongs to a department with usage deviations from matching meeting rooms, and the stable profile type of the department with usage deviations, and in conjunction with the control processing method, the reserved control meeting room in the meeting room is determined.

[0011] Secondly, the present invention provides a logistics service management system, employing the aforementioned logistics service management method, specifically including: The control method determination module, the control processing module, and the identification processing module are all included. The control method determination module is responsible for determining the control and processing method for the conference room. The control and management processing module is responsible for determining whether it is necessary to identify and process the control and management optimization objectives in the conference room; The identification and processing module is responsible for determining the identification and processing method for the conference room as a management and control optimization target.

[0012] Other features and advantages will be set forth in the following description, and the objects and other advantages of the invention are realized and obtained through the structures particularly pointed out in the description and the drawings.

[0013] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0014] The above and other features and advantages of the present invention will become more apparent from a detailed description of exemplary embodiments thereof with reference to the accompanying drawings.

[0015] Figure 1 This is a flowchart of a logistics service management method; Figure 2 This is a flowchart illustrating the methods for determining the management and control procedures for meeting rooms; Figure 3 This is a flowchart illustrating the method for determining the reservation and control of meeting rooms; Figure 4 This is a flowchart for identifying and processing the objectives that need to be optimized for management in the meeting room; Figure 5 This is a framework diagram of a logistics service management system. Detailed Implementation

[0016] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Based on the embodiments of this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this specification.

[0017] Example 1 like Figure 1 As shown, this application provides a logistics service management method, specifically including: S1 determines the availability of meeting rooms on different dates based on meeting room booking data, and determines the management and control method for the meeting rooms by combining the matching of available meeting rooms with the meeting needs of different departments. Furthermore, the meeting room booking data is determined based on meeting rooms booked on different dates.

[0018] Furthermore, the availability of the meeting room is determined based on the dates on which the meeting room is not booked.

[0019] Specifically, such as Figure 2 As shown, the method for determining the control and management method of the conference room is as follows: This embodiment aims to provide a refined method for managing meeting room resources. Its core decision-making objective is to dynamically adjust the level of control over meeting room resources based on historical usage data, optimizing overall resource utilization efficiency while ensuring the core meeting needs of each department. The core logic lies in not only assessing the overall availability of meeting room resources but also deeply analyzing the matching between available resources and the historical usage habits of each department, and predicting the impact of different levels of control on each department. By integrating these three dimensions, the decision-making logic aims to achieve a balance: when the impact of control on each department is low, stronger control is implemented to improve order and efficiency; when the impact of control on certain departments is high, weaker control is implemented to avoid excessive interference with their core business.

[0020] S11 determines the number of available meeting rooms on different dates based on the availability of meeting rooms on different dates; The number of available meeting rooms refers to the total number of meeting rooms that are not booked for each individual date within a set statistical analysis period.

[0021] This step aims to obtain the most basic and objective macroeconomic indicators of resource availability. Daily statistics generate a time-series data set to describe the overall supply level and fluctuations of the resource pool. This indicator serves as the starting point for all subsequent analysis and decision-making. It transforms the complex, instantaneous resource status into a quantifiable and comparable time series, providing primary data support for assessing overall resource scarcity and ensuring that decisions are based on objective facts rather than subjective feelings.

[0022] A concrete example: Suppose an organization has 15 meeting rooms, and we retrieve its booking records for the past 20 working days. The system scans each day, for example, finding that 5 meeting rooms were not booked all day on the first day, 3 were not booked on the second day, and so on, eventually obtaining a sequence of 20 values ​​[5, 3, 8, 4, 2, ...]. This sequence represents the number of available meeting rooms on different dates.

[0023] S12 determines the matching department for the vacant meeting room based on the matching situation between the vacant meeting room and the meeting needs of different departments; It should be noted that the matching department for the available meeting room is determined based on the number of times the available meeting room is used in that department. Specifically, departments with a usage count greater than a preset usage count threshold are selected as the matching departments.

[0024] The matching department is defined for a specific meeting room. If a department's actual usage frequency of a meeting room exceeds a preset threshold within a historical statistical period, then that department is identified as a matching department for that meeting room. This indicates a strong usage correlation between the meeting room and the department.

[0025] This step introduces the dimensions of "quality" and "inertia" in resource allocation. Meeting rooms are not entirely homogeneous; departments may have preferences or established usage habits for specific meeting rooms (perhaps due to location, equipment, or size). By defining matching relationships through historical usage frequency, we can identify the departments most "dependent" on each meeting room. This allows resource management strategies to consider these deeper needs, linking abstract "departmental needs" with specific physical resources, thus concretizing those needs. This enables subsequent analysis to assess whether "idle resources" truly represent "resources needed by each department," thereby elevating the management strategy from a "quantitative" management level to a "qualitative" adaptation level.

[0026] For example, taking the "Second Meeting Room" as an example, historical data shows that the "Marketing Department" used the meeting room 30 times, the "Technology Department" used it 12 times, and the "Finance Department" used it 5 times. If the preset usage threshold is 20, then only the "Marketing Department" (30 times > 20 times) is considered a matching department for the "Second Meeting Room". This means that when the "Second Meeting Room" is idle, its value to the Marketing Department is far greater than that to other departments.

[0027] S13 determines the management and control method for the meeting rooms based on the number of available meeting rooms on different dates and the matching departments of the available meeting rooms.

[0028] It is understandable that if the average number of available meeting rooms on different dates is greater than a preset threshold for the number of available meeting rooms, then a preset control method will be used to determine the control and processing method for the meeting room.

[0029] The core of this step lies in a tiered decision-making logic. First, the overall resource availability is assessed to determine the resource balance. Then, the fairness of allocation is assessed based on the matching situation. Finally, the impact of different control strategies is estimated to determine the final control level. The logic for assessing the impact level is as follows: if control is implemented (meaning some meeting rooms are restricted from booking), the business of matching departments that frequently use the controlled meeting rooms in the near future will be significantly impacted, i.e., the impact level is high; conversely, the impact level is low. To minimize interference with core business, when the impact level is high, the number of controlled meeting rooms should be reduced (i.e., the second preset number should be selected); when the impact level is low, the number of controlled meeting rooms can be increased (i.e., the preset number should be selected).

[0030] The average number of available meeting rooms per day within the statistical period is calculated and compared with a preset threshold for the number of available meeting rooms. If the average is greater than the threshold, it is determined that the overall resources are very abundant, and the preset control method with stronger control measures (i.e., controlling a preset number of meeting rooms) is directly adopted. If the average is not greater than the threshold, the process enters the refined matching analysis stage.

[0031] This is the most efficient macro-level filter. When overall resource supply far exceeds demand, the main challenges are improving utilization and establishing order. Strong control can be implemented without complex analysis, resulting in high decision-making efficiency and rapid response to the macro-level state of resources. In scenarios with extremely abundant resources, the decision-making process is simplified.

[0032] Additionally, it's understandable that if the average number of available meeting rooms across different dates does not exceed a preset threshold for the number of available meeting rooms, the following will also apply: Scenario 1: Based on the matching departments of available meeting rooms on different dates, if it is determined that all departments have available meeting rooms as matching departments on different dates, then the preset control method is used to determine the control and processing method of the meeting room.

[0033] On each date within the statistical period, all departments have at least one available meeting room that matches them, using a pre-defined control method.

[0034] Even with a tight overall supply, the daily available resources perfectly match the historical needs of each department, indicating that the current allocation model has achieved a highly idealized state of fairness. Maintaining strong control also has a relatively small impact on the overall situation; therefore, a strong regulatory model is adopted.

[0035] Scenario 2: If there are not equal available meeting rooms for matching departments in all departments on different dates, the available meeting room for each department is determined based on the percentage of dates in which available meeting rooms for matching departments exist. Departments with available meeting room coefficients not greater than a preset matching coefficient threshold are designated as matching deviation departments. If the number of matching deviation departments is greater than a preset matching deviation department number threshold, a preset control method is used to determine the control and processing method for the meeting room.

[0036] The idle matching coefficient refers to the proportion of days within a statistical period when a specific department has an idle meeting room that matches itself as the matching department, out of the total number of statistical days. A matching deviation department refers to a department whose idle matching coefficient is not greater than a preset matching coefficient threshold.

[0037] This coefficient quantifies how easily a department can obtain its "favored" meeting room. The lower the coefficient, the more disadvantaged the department is in resource competition. In this case, a strong management approach is adopted to improve the reliability of meeting room usage and prevent a single meeting room from being frequently used by certain departments.

[0038] Case 3: If the number of departments with matching deviations is not greater than the preset threshold for the number of departments with matching deviations, then the second preset control method is used to determine the control and processing method for the conference room.

[0039] If the number of departments with matching deviations is no greater than the preset threshold for the number of departments with matching deviations, meaning that only a few departments have matching deviations, then in this case, the second preset control method must be adopted to reduce the impact of control on different departments obtaining their optimal meeting room.

[0040] It should be noted that the preset control method is to manage a preset number of meeting rooms, and the second preset control method is to manage a second preset number of meeting rooms, wherein the preset number is greater than the second preset number.

[0041] Suppose a company has 10 meeting rooms numbered RM01 to RM10, representing four business departments: A, B, C, and D. Based on the booking data of the past 30 calendar days, determine the meeting room management strategy for the future.

[0042] Preset control method: Control measures will be implemented for 5 meeting rooms (preset quantity = 5).

[0043] Second preset control method: Control measures will be implemented for 2 meeting rooms (second preset quantity = 2).

[0044] Implementation process: Execute S11: The system analyzes data from the past 30 days to calculate the number of available meeting rooms per day, and the average number is 2.1.

[0045] Top-level judgment: The average value of 2.1 is not greater than the threshold of 3, indicating overall resource shortage, and entering refined matching analysis.

[0046] Execute S12: The system analyzes the historical usage records of each meeting room. For example, RM01 was used 18 times by Department A and 5 times by Department B, therefore Department A is the matching department for RM01. Similarly, the matching departments for all meeting rooms are determined.

[0047] Scenario 1: System checks revealed that not all departments had available meeting rooms for all dates. For example, on several days, Department D had no available meeting rooms for any of its matched departments. Scenario 1 is not met.

[0048] Entering scenario 2, execute sub-step 1: The system calculates the idle matching coefficient for each department.

[0049] Department A: There are available meeting rooms for 22 out of 30 days, with a coefficient of 22 / 30 ≈ 0.73. Department B: There are available meeting rooms for 18 days, with a coefficient of 0.60. Department C: There are available meeting rooms for 20 days, with a coefficient of 0.67. Department D: There are available meeting rooms for 10 days, with a coefficient of 0.33.

[0050] Based on the preset matching coefficient threshold of 0.5, department D (0.33≤0.5) is identified as a department with a matching deviation.

[0051] Execution Scenario 2, Sub-step 2: The number of departments with matching deviations is 1, which is not greater than the preset threshold of 1 for the number of departments with matching deviations. Therefore, we proceed to Scenario 3. If strong control (preset control method) is implemented on 5 meeting rooms at this time, the selection range of meeting rooms will be reduced, which will have a high impact on their business. To reduce this impact, the system decides to adopt the second preset control method, that is, to implement control on only 2 meeting rooms.

[0052] The system selects two meeting rooms (e.g., RM08 and RM10) based on an algorithm, and applies rules to their application approval and near-term usage restrictions. The remaining eight meeting rooms remain freely available for booking. This solution maintains a certain level of management order while preserving ample resource options for the high-demand, high-impact Department D.

[0053] S2 determines the profile stability type of the department's meeting needs based on the department's meeting booking data. Based on different profile stability types, the department's meeting room usage data and management and control methods, the booking and management of meeting rooms on different dates is determined. When it is determined that the management and control optimization targets in the meeting rooms need to be identified and processed based on the management and control data and usage data of the meeting rooms on different dates, the process proceeds to the next step. Specifically, the stable types of the meeting needs profiles for the aforementioned departments include stable needs profiles, general stable profiles, and change profiles.

[0054] Specifically, the stability type of the department's meeting needs profile is determined based on the number of times different meeting rooms meet the department's meeting needs, including: This method involves creating in-depth profiles of meeting room usage patterns across departments and categorizing departmental meeting needs based on stability. The core logic lies in quantitatively analyzing the contribution of different meeting rooms to meeting the historical meeting needs of specific departments, thus classifying departments into different stability types from a "demand-resource" matching perspective. This approach aims to provide more refined input for resource allocation and management strategies, identifying departments with "stable needs" that are heavily reliant on specific meeting rooms, as well as departments with "changing needs" whose demand patterns are dispersed and flexible. This ultimately upgrades management decisions from "facing homogeneous departments" to "distinguishing departmental characteristics."

[0055] S21 determines the demand matching coefficient of the meeting room based on the proportion of the number of times the different meeting rooms meet the meeting needs of the department in the total number of meeting needs of the department; The demand matching coefficient is specific to a particular department and a particular meeting room. Its value equals the number of times the meeting room was used by the department (i.e., to meet its meeting needs) within a historical statistical period, divided by the total number of times the department used all meeting rooms within the same period. It characterizes the contribution rate of the meeting room to meeting the department's historical needs.

[0056] This step aims to break down a department's overall needs into specific meeting room resources. By calculating the proportions, it becomes clear which meeting rooms are the department's primary resources and which are secondary or occasional resources, thus accurately depicting the department's demand distribution structure.

[0057] It provides the quantitative foundational data for profiling departmental needs. Through this coefficient matrix (department × meeting room), the importance of different meeting rooms to the same department, as well as the differences in the importance of the same meeting room to different departments, can be intuitively compared, enabling needs analysis to move from qualitative description to quantitative analysis.

[0058] Considering that Department A used Meeting Room A 50 times, Meeting Room B 30 times, and other meeting rooms a total of 20 times in the past 100 meeting room usage records, then for Department A, the demand matching coefficient for Meeting Room A is 50 / 100 = 0.5; the coefficient for Meeting Room B is 30 / 100 = 0.3; and the coefficients for other meeting rooms are all less than or equal to 0.2. This shows that Department A's demand is highly concentrated in Meeting Room A.

[0059] S22 If the department has a meeting room with a demand matching coefficient greater than a preset matching coefficient threshold, then the meeting demand profile of the department is determined to be a stable demand profile. For the department being analyzed, determine whether there are meeting rooms whose demand matching coefficient is greater than the preset matching coefficient threshold. If so, determine that the meeting demand profile of the department is a stable demand profile.

[0060] The stable demand profile refers to departments whose historical meeting needs are highly concentrated in one or a very few meeting rooms. These departments have developed a strong dependence on or preference for specific meeting rooms, and a preset matching coefficient threshold sets a high concentration threshold. When the matching coefficient of a department's meeting room demand exceeds this threshold, it indicates that the meeting room handles the vast majority of the department's meeting needs, and the department's demand pattern is highly focused and predictable.

[0061] Continuing the previous example, if the preset matching coefficient threshold is set to 0.4, then the matching coefficient for Department A's demand for "Meeting Room A" is 0.5, which is greater than 0.4. Therefore, Department A is determined to be a stable demand profile type. This means that Department A's demand pattern is stable and concentrated, and during resource scheduling, the matching priority between "Meeting Room A" and Department A should be set to the highest.

[0062] S23 If the department does not have a meeting room with a demand matching coefficient greater than a preset matching coefficient threshold, obtain the maximum value of the demand matching coefficient of different meeting rooms, and determine whether the maximum value of the demand matching coefficient of the meeting room is less than the preset matching coefficient value. If yes, determine that the stable type of the meeting demand profile of the department is a variable profile; otherwise, determine that the stable type of the meeting demand profile of the department is a general stable profile.

[0063] There are no meeting rooms in the department that meet the conditions of step S22 (i.e., the demand matching coefficient of all meeting rooms is not greater than the preset matching coefficient threshold).

[0064] Sub-step: Obtain the maximum value among all demand matching coefficients for all meeting rooms in this department. Compare this maximum value with a lower preset matching coefficient value.

[0065] Decision logic: If the maximum value is less than the preset value of the matching coefficient: determine that the stable type of the meeting needs profile of this department is the variable profile.

[0066] If the maximum value is not less than the preset value of the matching coefficient: determine that the stable profile type of the meeting needs of this department is a general stable profile.

[0067] Change profile: This refers to departments whose historical meeting needs are highly dispersed, with no single department heavily reliant on meeting rooms. Their needs are relatively evenly distributed across the various meeting rooms.

[0068] Typical stable profile: This refers to departments whose demand has a certain tendency to be concentrated, but the concentration level does not reach the level of "stable demand". They may have two or three frequently used meeting rooms, but they do not have an absolute dependence on any single meeting room.

[0069] When departmental demand is not concentrated enough (not reaching a high threshold), it is necessary to further distinguish between "relatively concentrated" and "completely dispersed." A preset matching coefficient serves as a low baseline to determine whether a department has a relatively primary option. A maximum value below this line indicates that there is no relatively primary option, and demand is highly volatile; conversely, a maximum value above this line indicates the existence of a relatively primary option with general stability.

[0070] In a possible specific embodiment, consider "Department B," whose historical 100 requests are distributed across 5 meeting rooms: Meeting Room C (25 requests, coefficient 0.25), Meeting Room D (22 requests, coefficient 0.22), Meeting Room E (20 requests, coefficient 0.20), Meeting Room F (18 requests, coefficient 0.18), and Meeting Room G (15 requests, coefficient 0.15). Assume a preset matching coefficient threshold of 0.4 and a preset matching coefficient value of 0.3. First, all coefficients are no greater than 0.4, failing to meet the stable demand profile condition. Then, its maximum demand matching coefficient is 0.25, which is less than 0.3. Therefore, the administrative department is judged as a variable profile type, with highly flexible demands.

[0071] Furthermore, such as Figure 3 As shown, the method for determining the reserved and controlled meeting room is as follows: This approach precisely and reasonably maps macro-level control decisions (i.e., the number of meeting rooms requiring control) to specific physical meeting rooms. Its core logic is to minimize the impact on departments that have not recently met their meeting room usage needs, aiming to select the meeting rooms for control. To achieve this goal, the method first identifies departments with low recent usage (departments with usage bias, i.e., departments unable to effectively meet their needs) and identifies their historically preferred meeting rooms. Then, through a set of protective rules and a quantitative screening mechanism, it systematically excludes or avoids selecting these "historically preferred meeting rooms that have not recently met their needs" as control targets. This ensures that control measures primarily target meeting rooms with a weaker historical correlation to recent ineffective demand fulfillment, achieving a balance between control efficiency and operational stability.

[0072] S31 uses different profile stability types and departmental meeting room usage data to determine the number of times the meeting room of the department was used within the most recent preset duration, and determines the departments with usage deviations in the department based on the number of times of use. Departments with usage deviations are those whose total number of meeting room uses (i.e., the number of times a reservation has been made and successfully used) is less than a preset usage threshold within the most recent preset time period. This indicator is used to quantify whether a department has effectively met its needs in the most recent period.

[0073] "Recent Preset Duration" ensures that the assessment reflects the department's current or recent activity level, rather than its long-term historical status, making the judgment more timely. "Number of Uses" more accurately reflects activity frequency than "Number of Days Used." Setting thresholds objectively defines a quantitative standard for "recently unmet needs," which is the starting point for the "impact minimization" strategy. Identifying departments that have not recently had their needs effectively met means that they have not received effective support recently, avoiding restrictions on matching them with meeting rooms.

[0074] S32 determines that the meeting room belongs to the department with the usage deviation based on the degree of matching between the meeting room and the usage deviation of the department. The "Department with a Usage Deviation in Meeting Room Usage" attribute is defined for a specific meeting room. If a department with a usage deviation uses a meeting room a certain number of times in historical data, that department is identified as having this attribute for that meeting room. This indicates that the meeting room is one of the meeting rooms that the department has historically "favored" or "used" without recently meeting its needs.

[0075] For departments that haven't been effectively meeting their needs recently, it's also necessary to understand their historical resource preferences. Even if a department hasn't been effectively meeting its needs recently, its historically preferred meeting rooms still hold special significance. Avoiding control over such meeting rooms reserves space for future needs, establishing a strong historical correlation graph between "specific meeting rooms" and "departments that haven't been effectively meeting their needs recently." This allows subsequent screening to be based on specific relationships, rather than vague departmental categories, leading to more refined decision-making.

[0076] S33 determines the reserved control meeting room in the meeting room by considering the department with the deviation in using the matching meeting room, the stable profile type of the department with the deviation in using the meeting room, and the control processing method.

[0077] It should be noted that the "deviation department" refers to the department whose meeting room usage frequency within the most recent preset time period is less than a preset usage frequency threshold.

[0078] Specifically, the meeting room is determined by the department that uses the matching meeting room according to whether the meeting room meets the department's meeting needs, and is selected from meeting rooms that have been used more than a preset number of times.

[0079] It is understood that, based on the fact that the meeting room belongs to a department with usage deviations from matching meeting rooms, and the stable profile type of the department with usage deviations, and in conjunction with the control processing method, the reserved control meeting rooms in the meeting room are determined, specifically including: S331. Based on the proportion of the meeting room belonging to the department with usage deviation in the matching meeting room among all departments with usage deviation, determine the matching ratio, and determine whether the matching ratio is greater than the preset matching ratio threshold. If yes, determine that the meeting room does not belong to the reservation control meeting room; otherwise, proceed to step S332. Matching ratio refers to the proportion of departments with usage deviations that use a specific meeting room relative to the total number of departments with usage deviations in the system. The preset matching ratio threshold is a set upper limit for the ratio.

[0080] If a meeting room is a historically preferred meeting room that has been largely underutilized recently, then it essentially serves as a "potential public backup resource" for these departments. Controlling such meeting rooms is tantamount to simultaneously depriving a large number of departments that have recently underutilized their meeting rooms of a potential core backup resource, posing a high systemic risk. When a meeting room is too widely associated with departments that have recently underutilized it, it should be directly excluded from the control candidate list to prevent widespread potential dissatisfaction or future resource shortages.

[0081] S332 Based on the stable profile type of the meeting room belonging to the department with the deviation of the use of the matching meeting room, determine whether there is a department with the stable profile type of stable demand profile among the departments with the deviation of the use of the matching meeting room. If yes, determine that the meeting room does not belong to the reservation control meeting room. If not, proceed to step S333. For meeting rooms filtered by S331 (i.e., meeting rooms with a low matching ratio), check whether there are departments with stable demand profiles among the departments that use the matching meeting rooms and have a stable profile type.

[0082] Departments with stable demand profiles are highly dependent on their preferred meeting rooms. These departments have not been effectively meeting their needs recently, focusing instead on historically preferred meeting rooms. Controlling their core resources would significantly hinder their business recovery; therefore, departments with special dependencies should receive focused protection. This reflects a differentiated and human-centered strategy, acknowledging and protecting the inherent, stable working patterns of different departments.

[0083] S333 Obtain the number of meeting rooms excluding those not belonging to the reservation management meeting room, and determine whether the number of meeting rooms excluding those not belonging to the reservation management meeting room is less than the number of meeting rooms to be managed by the management processing method. If so, the remaining meeting rooms are all managed and processed. If not, proceed to step S334. Compare this remaining quantity with the number of meeting rooms to be managed as specified in the management method (i.e., the preset quantity or the second preset quantity). If the remaining quantity is less than the required quantity, then all remaining meeting rooms are designated as reserved management meeting rooms.

[0084] This is a step that satisfies the hard constraints of management. When there are not enough candidate meeting rooms that meet the "safety" criteria, it means that the control indicators cannot be completed without violating the protection rules. At this time, control can only be implemented on all existing optimal sets. This is the optimal solution under the constraints of reality, ensuring the executability of management instructions. It is a necessary link in the logical closed loop and prevents the deadlock of not being able to select enough control targets.

[0085] S334 determines the weight value of the department with usage deviation based on the stable profile type of the meeting room belonging to the department with usage deviation of the matching meeting room. The matching weight value of the meeting room is determined by the sum of the weight values ​​of the departments with usage deviation of the matching meeting room. The meeting room with the smallest matching weight value is selected as the meeting room for management and control under the number of meeting rooms for management and control processing corresponding to the management and control processing method.

[0086] Determine weight values: Assign a weight value to each stable profile type (e.g., stable demand profile = 3, generally stable profile = 2, variable profile = 1). Calculate matching weight values: For each candidate meeting room, sum the weight values ​​of all departments with usage deviations that use the matching meeting room to obtain the matching weight value for that meeting room. This value comprehensively reflects the historical correlation strength between the meeting room and departments that have not recently had their needs effectively met, as well as the stability of those departments' needs. The higher the value, the stronger and more stable the correlation, and the greater the potential negative impact of control measures.

[0087] Optimal selection: Sort all candidate meeting rooms by their matching weight value from smallest to largest, and select the meeting room with the highest ranking and the number equal to the required number of control rooms as the final booking and control meeting room.

[0088] When multiple "safe" meeting rooms are available, this step achieves "selection of the best among the best." It selects meeting rooms that are least associated with departments whose needs have not been effectively met recently, or whose needs are least stable, for management, thereby minimizing the potential long-term negative impact of management. Under the premise of satisfying all protective constraints, it achieves global optimization of management objective selection, which is the ultimate manifestation of refined decision-making.

[0089] The finalized reservation control meeting rooms will be subject to control, with the specific rule being: "Departments that have used the meeting room within the most recent preset duration will not be allowed to make new reservations."

[0090] This rule is consistent with the aforementioned screening logic. The screening logic protects the historical preferences of departments whose needs have not been effectively met recently (avoiding long-term impact), ensuring that control has almost no impact on current and past normal usage patterns, and only adjusts for new future booking behavior. This execution rule constitutes a complete and self-consistent control strategy closed loop, so that the decision-making idea of ​​"minimizing negative impact" is thoroughly implemented at the final execution end.

[0091] It should be noted that when a meeting room is subject to control and management, the meeting room will be subject to control and management, and departments that have used the meeting room within the most recent preset time period will not be allowed to make reservations.

[0092] Assume an organization has 6 departments (D1-D6) and 8 meeting rooms (R1-R8). Preliminary analysis has revealed the stability type of each department: D1 (Stable), D2 (Neutral), D3 (Variable), D4 (Stable), D5 (Neutral), and D6 (Variable). Based on management decisions, it is now necessary to control 3 meeting rooms (preset quantity = 3).

[0093] Data preparation and execution: S31 Result: Based on recent usage counts, D1 (2 times), D3 (1 time), and D5 (3 times) are all below the threshold of 4 and are therefore classified as departments with usage deviations. There are a total of 3 such departments.

[0094] S32 Result: Based on historical data (usage times ≥ 15 times), determine the historical matching meeting rooms for each department with usage deviation: D1 (Stable) matches meeting room R2; D3 (Variable) matches meeting room R4; D5 (Normal) matches meeting room R4, R6. Therefore: the related departments of R2 are {D1}, the related departments of R4 are {D3, D5}, and the related departments of R6 are {D5}. S33 Filtering: S331: The total number of departments with deviations is 3. R2 matching ratio = 1 / 3 ≈ 0.33 < 0.5, passed. R4 matching ratio = 2 / 3 ≈ 0.67 > 0.5, failed, R4 is excluded. R6 matching ratio = 1 / 3 ≈ 0.33 < 0.5, passed.

[0095] S332: Inspect the meeting rooms (R2, R6 and others) that pass through S331.

[0096] R2's associated department D1 is "Stable Demand Profile," which exists, therefore R2 is excluded.

[0097] R6's associated department D5 is "General Stable Profile". There is no "Stable" department. Approved.

[0098] Other meeting room associations are empty; approved.

[0099] Current candidate pool: R1, R3, R5, R6, R7, R8 (6 in total).

[0100] S333 Decision: 3 companies need to be managed, there are 6 companies in the candidate pool, 6>3, proceed to S334.

[0101] S334 Calculation and Selection: Calculate the matching weight value for each candidate meeting room (only R6 has an associated department D5, so its weight is 2; the others are 0): R1:0, R3:0, R5:0, R6:2, R7:0, R8:0 Sort by value (for values ​​with the same value, sort by number): R1(0), R3(0), R5(0), R7(0), R8(0), R6(2) The first three rooms selected—R1, R3, and R5—were designated as the reserved and controlled meeting rooms.

[0102] The system implements controls on R1, R3, and R5. The rule is in effect: From now on, any department that has used these three meeting rooms within the past 10 business days will be unable to book the same meeting room. This rule protects the continued usage rights of recently active users while encouraging resources to flow to other meeting rooms.

[0103] S3 determines the degree of matching of the meeting room's needs with different departments, and, in combination with the demand matching of different departments with meeting rooms that cannot be used as management optimization targets, determines the identification and processing method for the meeting room as a management optimization target.

[0104] Furthermore, such as Figure 4 As shown, the identification and processing of the control optimization objectives in the conference room are determined, specifically including: S41 determines the management and processing date of the meeting room based on the management and processing data of the meeting room on different dates; Control and processing dates refer to the set of dates within a selected historical analysis period on which control and processing methods were actually implemented for a specific meeting room.

[0105] This step is the data preparation stage for quantitative effect evaluation. It transforms the Boolean state of "whether the meeting room is under control" into a specific distribution record on the timeline, providing basic data for subsequent calculations of indicators such as frequency and proportion. It converts the history of management operations into structured, analyzable time-series data, making it possible to objectively evaluate the intensity, mode, and effectiveness of control.

[0106] For example: During a one-month analysis period (30 days), the system log shows that "Meeting Room α" was set as a reserved and controlled meeting room and the corresponding rules were executed on the 5th, 12th, 19th, and 26th. Therefore, the set of control processing dates for Meeting Room α is {5, 12, 19, 26}.

[0107] The above steps include the following: S411 The meeting room with the date of management and control processing is designated as the management and control meeting room. It is determined whether the proportion of the management and control meeting room in the meeting room is less than the preset management and control meeting room proportion threshold. If so, it is determined that no management and control optimization target identification processing is required in the meeting room. If not, proceed to step S412. Controlled meeting rooms refer to meeting rooms whose set of controlled processing dates is not empty within the analysis period, i.e., meeting rooms that have been controlled for at least one day. The preset controlled meeting room ratio threshold is a benchmark value used to determine whether the control scope is universal.

[0108] This step first examines the general applicability of the control strategy. If only a small number of meeting rooms are under control, it indicates that the control is a localized or experimental measure with limited overall impact, and does not yet constitute a sufficient condition to initiate a system-level optimization process, acting as an efficient cost control filter. It avoids expending resources on complex downstream analysis when the control measure itself has a small scope of application, aligning with the principle of economic efficiency in management and improving system operational efficiency.

[0109] S412 Based on the management and processing dates of different meeting rooms, determine the proportion of the management and processing dates of the meeting rooms and use it as the management proportion. Determine whether there are meeting rooms with a management proportion greater than the preset management proportion threshold. If yes, proceed to step S42. If no, determine that it is not necessary to identify and process the management and optimization targets in the meeting rooms. The control ratio refers to the proportion of days a meeting room is under control relative to the total number of days in the analysis period. Meeting rooms affected by control are those with a control ratio exceeding a preset control ratio threshold; even with broad control coverage, the distribution may be even. This step aims to identify specific meeting rooms that are being controlled "abnormally frequently" or "for a long time." The continuous control of individual meeting rooms often points to ongoing resource competition or allocation conflicts, representing potential problem areas. This shifts the analytical perspective from a global "surface" of coverage to the "points" where problems may arise. Only when meeting rooms are found to be controlled with abnormally high frequency does it mean that specific, persistent problems warrant in-depth examination and optimization.

[0110] S42 uses the usage data of the meeting room during the management and control processing period to determine the usage date of the meeting room during the management and control processing period; In the above steps, meeting rooms with a control ratio greater than the preset control ratio threshold are identified as meeting rooms affected by control. The proportion of usage dates of different meeting rooms affected by control is used to determine the usage date ratio. It is then determined whether there are meeting rooms affected by control with a usage date ratio less than the preset ratio threshold. If so, proceed to step S43. If not, it is determined that no identification and processing of control optimization targets in the meeting rooms is required. Usage Dates specifically refer to the dates a meeting room is successfully booked and actually used within its controlled processing dates. The Usage Dates Ratio is calculated for a controlled-impact meeting room and is equal to the number of its Usage Dates divided by the total number of its controlled processing dates.

[0111] This step is central to the effectiveness evaluation, aiming to verify whether the control measures have achieved the expected goal of "restricting non-targeted use." An extremely low utilization rate of a meeting room on the controlled dates suggests that the control may be excessive, leading to resource underutilization; conversely, an extremely high utilization rate may indicate that the control rules have been circumvented or are ineffective. It establishes a correlation between administrative records of control measures and actual usage effectiveness, serving as a key indicator for judging whether control measures are "overcorrected" or "ineffective," and providing direct evidence of effectiveness for optimization decisions.

[0112] S43 determines whether it is necessary to identify and process the management optimization targets in the meeting rooms based on the management and control processing dates of different meeting rooms and the usage dates of the meeting rooms within the management and control processing dates.

[0113] Specifically, the above steps include the following: S431 determines whether the number of meeting rooms affected by the control measures is greater than the preset control quantity threshold. If yes, it is determined that the control optimization target in the meeting room needs to be identified and processed. If no, proceed to step S432. The system counts the number of meeting rooms affected by control measures whose usage date ratio is less than a preset threshold. If this number exceeds the preset control quantity threshold, it is determined that the control optimization targets in the meeting rooms need to be identified and processed.

[0114] When multiple frequently controlled meeting rooms experience severe usage suppression simultaneously, it indicates that "over-control" is not an isolated incident but a widespread systemic problem with clear and serious risks. Therefore, it is necessary to establish a rapid response mechanism for widespread and significant problems and improve the system's judgment and response speed to clear risks.

[0115] S432 determines the control impact value based on the number of meeting rooms affected by the control measures, the control ratio of different control impact meeting rooms, and the number of control impact meeting rooms whose usage date ratio is less than a preset ratio threshold. When the control impact value is greater than the preset impact threshold, it is determined that the identification and processing of control optimization targets in the meeting rooms need to be carried out.

[0116] The Control Impact Value is a comprehensive quantitative indicator used to characterize the overall severity of the potential negative impacts of current control measures. Its calculation formula is: Control Impact Value = (Number of meeting rooms affected by control measures + Number of meeting rooms affected by control measures whose usage date ratio is less than a preset threshold) × (Average control ratio of all meeting rooms affected by control measures).

[0117] When the number of problematic meeting rooms is small, a more refined assessment of the "quality" and "quantity" of their impact is needed. This formula comprehensively considers the "number of meeting rooms that are frequently controlled" (breadth), the "number of meeting rooms that are severely suppressed in use" (intensity), and the "average control frequency" (depth). The product of these three factors can better reflect the overall scale of the impact.

[0118] It provides a precise tool for quantifying trade-offs in critical situations. Even if the number of problem rooms is small, if they are managed too frequently and excessively, their combined impact may exceed a threshold, triggering optimization and preventing the omission of important, critical local problems.

[0119] It is understood that the control impact value is determined by multiplying the sum of the number of control impact meeting rooms and the number of control impact meeting rooms whose usage date ratio is less than a preset ratio threshold, with the average control ratio of different control impact meeting rooms.

[0120] Suppose a company has 10 meeting rooms (R1-R10). Based on the management and usage data of the past 30 calendar days, determine whether an optimization process needs to be initiated.

[0121] Implementation process: Execute S41: The system reads data from the past 30 days to determine the set of control and processing dates for each meeting room.

[0122] Execution S411: Statistics show that 5 meeting rooms (R1, R3, R5, R7, R9) have management records, meaning the number of managed meeting rooms is 5. The ratio is 5 / 10 = 0.5. 0.5 > the preset managed meeting room ratio threshold of 0.3, proceed to S412.

[0123] Execute S412: Calculate the control ratio of each controlled meeting room.

[0124] R1: Control for 22 days, ratio = 22 / 30 ≈ 0.73; R3: Control for 18 days, ratio = 0.60; R5: Control for 10 days, ratio ≈ 0.33; R7: Control for 25 days, ratio ≈ 0.83; R9: Control for 5 days, ratio ≈ 0.17 Compared to the preset control ratio threshold of 0.6, R1 (0.73>0.6), R3 (0.60=0.6), and R7 (0.83>0.6) were marked as affecting the meeting room.

[0125] Execute S42: For R1, R3, and R7, calculate their usage date ratio.

[0126] R1 was used for 4 out of 22 control days, a ratio of 4 / 22 ≈ 0.18.

[0127] R3 was used for 12 out of 18 control days, a ratio of approximately 0.67 (12 / 18).

[0128] R7 was used for 6 out of 25 control days, a ratio of 6 / 25 = 0.24.

[0129] Compared to the preset ratio threshold of 0.35, the ratios of R1 (0.18<0.35) and R7 (0.24<0.35) are lower than the threshold.

[0130] Execute S43: S431 Decision: There are 2 meeting rooms R1 and R7 whose usage date ratio is lower than the threshold. This number is equal to (not greater than) the preset control quantity threshold of 2, so proceed to S432.

[0131] S432 calculation: Number of meeting rooms affected by control = 3 (R1, R3, R7), Number of meeting rooms affected by control with usage date ratio less than the preset ratio threshold = 2 (R1, R7), Average control ratio = (0.73 + 0.60 + 0.83) / 3 ≈ 0.72.

[0132] The control impact value = (3 + 2) × 0.72 = 5 × 0.72 = 3.6. The control impact value 3.6 > the preset impact threshold 2.0. Therefore, the system determines that the control optimization target in the conference room needs to be identified and processed.

[0133] The trigger judgment method provided in this embodiment endows the conference room resource management system with self-monitoring and evaluation intelligence. Its value is reflected in the following aspects: First, it automates and objectifies the evaluation of management effectiveness by replacing subjective experience judgment with multi-layered data indicators, ensuring that the initiation of optimization processes is based on a reliable chain of evidence. Second, it embodies a balance between hierarchical decision-making and cost-effectiveness. Through layer-by-layer filtering in S411 and S412, unnecessary complex analysis is avoided, and optimization resources are only invested when management reaches a certain breadth and concentration and shows potential negative effects. Third, comprehensive quantitative evaluation ensures the accuracy of judgment, especially the calculation of management impact value in S432, which integrates the breadth, depth, and intensity of the problem, enabling the system to sensitively identify management problems that, although not widespread, have a serious impact. Fourth, it forms a complete "management-monitoring-optimization" closed loop, making management strategies no longer static settings, but an intelligent system that can dynamically respond and adjust based on execution results, promoting continuous optimization of resource allocation. Overall, this method improves the adaptability and refinement level of the conference room management system.

[0134] Furthermore, the method for determining the meeting room as the target for management and control optimization is as follows: In this embodiment, for each meeting room currently under control, the appropriate control optimization target identification and processing path is intelligently determined. This decision aims to establish a hierarchical and efficient decision funnel, classifying meeting rooms and guiding them to the most suitable identification method by assessing the inherent attributes of the meeting room, the resource status of related departments, and the overall stage of the system: direct exclusion, rapid confirmation, or detailed evaluation. This method ensures that the optimization identification process is safe, efficient, and accurate, avoiding the inefficiency or waste of resources of a "one-size-fits-all" approach.

[0135] S51 determines the department that uses the matching meeting room based on the degree of matching of the meeting room's needs in different departments, and identifies the department that uses the matching meeting room as the matching department. The above steps include the following situations: Scenario 1: If the number of matching departments in the meeting room is not less than the preset threshold for the number of matching departments, then the meeting room is determined to be unsuitable as a management optimization target. Once the management is lifted, some departments will use the meeting room for a long time, which will reduce the availability of the meeting room. In other words, there is no need to identify the meeting room as a management optimization target.

[0136] Matching departments refer to the set of departments in historical data that identify the meeting room as a match for their needs. A preset threshold for the number of matching departments is a high baseline value used to identify high-shared, high-risk meeting rooms; a preset value for the number of matching departments is a low baseline value used to identify low-shared, low-value meeting rooms.

[0137] The breadth of shared meeting rooms is one of its most stable attributes, directly correlated with the intensity of competition and the risk of monopoly after deregulation. By setting two thresholds, one high and one low, cases with extremely high risk and extremely low value can be quickly separated at the beginning of the decision-making process, thereby significantly simplifying the complexity of subsequent logic and constructing a highly efficient first-line classifier for identification method decision-making. Based on inherent data, it makes stable and rapid judgments, establishing a clear entry classification for the entire optimization process and significantly improving the system's processing throughput.

[0138] If the number of matching departments for a meeting room is not less than the preset threshold for the number of matching departments, the meeting room will be identified as "unable to be used as a control optimization target," meaning it will not be included in any subsequent identification and processing procedures.

[0139] An excessively high number of matching departments indicates that the meeting room is a "public good" within the organization. In an unregulated free market, "public goods" are most susceptible to overuse and "free-riding" problems, ultimately ending up occupied by a few of the most powerful "users." Maintaining control is a necessary means to combat this market failure and ensure broad and equitable access, setting inviolable "red lines" for system optimization and fundamentally preventing the systemic risk of large-scale unfair resource allocation caused by optimization.

[0140] Case 2: If the number of matching departments in the meeting room is less than the preset threshold for the number of matching departments, then determine whether the number of matching departments in the meeting room is less than the preset value for the number of matching departments. If yes, then determine that the meeting room is used as the basic meeting room for identification and processing of management and optimization targets. If no, then proceed to step S52. If the number of matching departments is less than the preset threshold for the number of matching departments, and further less than the preset value for the number of matching departments, then the identification method for this meeting room is determined to be "using it as a basic identification meeting room for management and optimization target identification processing".

[0141] The limited number of matching departments (e.g., 1-2) indicates a highly specialized service model for this meeting room. Removing its control will almost certainly not trigger cross-departmental resource competition, the negative impact is manageable and minimal, while the benefits (reduced management costs and increased departmental flexibility) are clear. Therefore, without consuming additional computing resources for complex assessments, directly prioritizing its removal is the most economical strategy. This enables instantaneous decision-making for simple, clear cases, significantly improving the overall efficiency of the optimization process and embodying the optimization philosophy of "simple problems, simple solutions."

[0142] S52 determines the number of matching meeting rooms used by the matching department, and uses the number of matching meeting rooms used to determine meeting rooms that cannot be used as management optimization targets; In the above steps, the departments whose number of matching meeting rooms is less than the preset threshold for the number of matching meeting rooms are considered as the affected departments. It is determined whether the proportion of the affected departments in the matching departments of the meeting room is greater than the preset threshold for the proportion of affected departments. If so, it is determined that the meeting room cannot be used as a control optimization target, that is, there is no need to perform the identification process as a control optimization target. If not, proceed to step S53. The number of matched meeting rooms used refers to the total number of departments whose needs match the overall meeting room resource pool for a given department. Departments affected are those whose number is less than the preset threshold for the number of matched meeting rooms. These departments have very limited meeting room resources available to them that match their preferences, and are in a resource-vulnerable state.

[0143] For meeting rooms that have passed the initial screening (i.e., the number of matched departments is moderate), it is necessary to assess the potential impact of optimization actions on their users. This step, from the user (department) perspective, identifies those "vulnerable" users with limited resources and poor risk resistance, preventing optimization actions from causing "secondary harm" to them. If there is too much optimization, i.e., free competition, the availability of their meeting rooms will inevitably be further compressed.

[0144] Calculate the percentage of affected departments among all matched departments in the current meeting room. If this percentage is greater than the preset threshold for the percentage of affected departments, then the meeting room will be identified as "unable to be used as a control optimization target".

[0145] If a meeting room's user base primarily consists of departments with limited resources, after deregulation, in a free competition environment, this meeting room is highly likely to be "snatched up" by more departments, exacerbating the plight of the vulnerable departments. This contradicts the original intention of optimization—to improve overall well-being.

[0146] S53 Based on the matching department of the meeting room and the data of meeting rooms that cannot be used as management optimization targets in the matching meeting rooms of different matching departments, the identification and processing method for determining the meeting room as a management optimization target is as follows.

[0147] Furthermore, the above steps include the following: S531 Based on the meeting rooms that cannot be used as management optimization targets, determine the proportion of meeting rooms that cannot be used as management optimization targets in the matching meeting rooms of different departments, and determine whether the proportion of meeting rooms that cannot be used as management optimization targets in the matching meeting rooms of different departments is greater than the preset meeting room proportion threshold. If so, determine that the identification and processing method of the meeting room as a management optimization target is to use it as the basic identification meeting room for management optimization target identification and processing. If not, proceed to step S532. The proportion of meeting rooms that cannot be used as optimization targets refers to the percentage of all matched meeting rooms in a department that have been determined by the system to be unsuitable for de-management (i.e., "unoptimizable"). A higher proportion indicates that the vast majority of the department's matched meeting rooms are under "management." Under management, the available competitors for each meeting room are restricted by rules, and the department faces a "low-competition" environment.

[0148] This step aims to identify sector groups that have deeply adapted to and benefited from a “low-competition-intensity” environment.

[0149] Department Status Analysis: Most of the matching meeting rooms for this type of department (e.g., 80%) are under control. Due to control rules (such as "restricting recent users" or approvals) filtering out a large number of potential competitors, the actual competition intensity faced by this department when booking these meeting rooms is low, resulting in a high success rate and a good usability experience.

[0150] Impact Assessment of Deregulating a Single Meeting Room: If control is deregulated from one meeting room (e.g., Meeting Room X), Meeting Room X will transition from a "low-competition environment" to a "free-competitive, high-competition environment." However, since the other 80% of the department's matching meeting rooms remain under control in a "low-competition environment," it still possesses a large number of highly available alternative resources. Therefore, the impact of losing Meeting Room X's "low-competition privilege" on the department's overall availability is minimal. Deregulation is a low-risk "nice-to-have," providing other departments with a competing resource.

[0151] Decision: If the proportion of all matching departments in the current meeting room is greater than the preset meeting room proportion threshold, then the decision is to use this meeting room as a basis for identifying and optimizing meeting rooms as management targets. This approach accurately identifies and promotes optimization measures that increase overall resource mobility without significantly harming existing high-availability departments, representing a Pareto improvement.

[0152] S532 selects departments whose proportion of meeting rooms that cannot be used as management optimization targets is no greater than a preset meeting room proportion threshold as screening departments, and determines whether there are screening departments among the matching departments of the meeting rooms. If yes, proceed to step S533; otherwise, determine that the identification and processing method of the meeting room as a management optimization target is to use it as the basic identification meeting room for management optimization target identification and processing. S533 determines the control demand factor of the meeting room based on the proportion of the screening departments in the matching departments of the meeting room and the proportion of meeting rooms in different screening departments that cannot be used as control optimization targets. It then determines whether the control demand factor of the meeting room is greater than the preset demand factor threshold. If so, it is determined that the meeting room cannot be used as a control optimization target, that is, no identification processing is required for it to be used as a control optimization target. If not, it is determined that the method for identifying the meeting room as a control optimization target is to identify it as a potential target for control optimization.

[0153] The screening department refers to a department whose proportion of meeting rooms that cannot be used as management optimization targets is not higher than the preset meeting room proportion threshold. The management intensity of such departments is relatively weak. Once the management is lifted, it may lead to a smaller selection of meeting rooms for them. This means that a considerable portion of the matching meeting rooms in this department (e.g., more than 30%) are already in an "optimizable" (i.e., they may be in a state of free competition) state.

[0154] S532: If no screening department is found among the matching departments in the meeting room, it means that all associated departments are "highly controlled, low-competitive" departments. This is consistent with the logic in S531, where removing control would have little impact on them; therefore, the decision-making process uses a "quick confirmation" identification method.

[0155] S533: If a screening department exists, it means that the meeting room is associated with some departments already in a "highly competitive environment." Removing control of this meeting room in this case will have an asymmetric impact: For "highly controlled" departments (non-screened departments): the impact is relatively small. For "screened departments": these departments have already lost many "controlled meeting rooms," and the remaining, controlled meeting rooms are crucial for maintaining their availability. Removing one of them would further deprive them of their scarce meeting room resources, forcing them into free competition, which could lead to a precipitous drop in their overall availability. This is an unacceptable risk.

[0156] Calculate the control demand factor. This factor is positively correlated with the "proportion of screening departments among the matching departments of the meeting room" (the more sensitive departments, the greater the overall risk), and negatively correlated with the "non-optimizable proportion of the screening departments themselves" (that is, the fewer "low-competition" resources the screening departments already have, the higher their vulnerability and the greater the risk).

[0157] If the control demand factor is greater than the preset demand factor threshold, it indicates that lifting the control will have a disastrous impact on the "screened departments". The decision must adopt the "direct exclusion" identification method to maintain control in order to protect the survival space of these departments.

[0158] If the factor is not greater than the threshold, it indicates that the risk is acceptable, but careful verification is required. The decision-making adopts a "fine assessment" identification method, which ensures that optimization is not based on affecting departments that are already at a competitive disadvantage, thus maintaining the stability of the resource allocation system.

[0159] After freely combining the meeting rooms (potential targets) entering the "refined assessment" path, multiple combinations are obtained. These combinations are then combined with the meeting rooms (basic identification meeting rooms) from the "quick confirmation" process to simulate and predict the meeting demand satisfaction rate of each department after batch de-control. Among the combinations with a satisfaction rate not lower than a preset satisfaction rate threshold, the scheme that can de-control the most people is selected for execution.

[0160] Furthermore, the higher the proportion of screening departments among the matching departments of the meeting room, and the lower the proportion of meeting rooms that cannot be used as management optimization targets for different screening departments, the higher the management demand factor of the meeting room. Since none of the matching meeting rooms of the screening departments are used as management meeting rooms, there may be situations where a certain department frequently uses the same meeting room in a short period of time, which makes it difficult to meet the requirements for the reliability of the meeting room use of the screening departments.

[0161] Furthermore, it is identified and processed as a potential target for management and optimization, specifically including: Multiple identification combinations are constructed by freely combining all the basic identified meeting rooms with the potential targets. The degree of matching of the meeting needs of all departments within the combination is determined when none of the meeting rooms in the combination are used as controlled meeting rooms within the target duration. This determines whether the combination can be used as a control optimization target.

[0162] Furthermore, determine whether it can be used as a target for management optimization, specifically including: When the meeting rooms in the combination cannot be used as management meeting rooms, and the meeting needs of all departments are satisfied at a rate greater than a preset satisfaction rate threshold, then the meeting room in the combination with the most meeting rooms can be used as the management optimization target.

[0163] The core decision-making objective of this embodiment is to determine whether meeting rooms previously identified as "fine-grained evaluation" targets (i.e., potential targets) can become management optimization targets through a mechanism of combined simulation and global satisfaction rate verification. This method constructs multiple sets of identification combinations, including basic identified meeting rooms and subsets of potential targets, and simulates a scenario where all meeting rooms in these combinations are deregulated within a target timeframe. The system then evaluates the matching degree of meeting needs across all departments in each scenario. The aim is to ensure that the final set of deregulated meeting rooms maximizes the release of management redundancy while absolutely guaranteeing that the overall availability of meeting resources within the organization does not experience a systemic decline, thereby achieving a safe and effective optimization decision-making closed loop.

[0164] 2. Explanation of steps, sub-steps, and specific operations Step S60: Construct the set of recognized combinations.

[0165] Key terms explained: "Basic identified meeting rooms" refers to the set of meeting rooms directly identified as requiring de-control during the initial decision-making process due to extremely low risk and clear value. "Potential targets" refers to the set of meeting rooms whose risk is controllable but requires further verification during the initial decision-making process. "Identification combination" is a set of meeting rooms consisting of all basic identified meeting rooms and any subset (including the empty set) of potential targets. Each combination represents a "batch de-control" scheme to be simulated and tested.

[0166] Specific example: Suppose that after preliminary decision-making, three basic identification meeting rooms (B1, B2, B3) and two potential targets (P1, P2) have been identified. Then, the possible identification combinations include: Combination C0: {B1, B2, B3} (basic objectives only), Combination C1: {B1, B2, B3, P1}, Combination C2: {B1, B2, B3, P2}, Combination C3: {B1, B2, B3, P1, P2}; The target duration refers to a future period of time for the simulation test (e.g., the next 30 working days). "Not under control" means that in a real-world usage scenario, all meeting rooms within the combination are assumed to be de-controlled and restored to their status as freely bookable regular meeting rooms.

[0167] In a real-world environment, the control status of all meeting rooms within the group is marked as "unlocked," and the matching degree of meeting needs for each department and the entire organization is calculated.

[0168] The degree of matching of meeting needs here specifically refers to the meeting requirement fulfillment rate. For a department, the fulfillment rate is equal to the number of times the department successfully booked a meeting room in a department that matches its needs within the target duration, divided by the total number of meeting requests. If the fulfillment rate of meeting needs for different departments is above 80%, then the combination is considered an available combination, and the meeting room in the available combination with the most meeting rooms is selected as the optimized and managed meeting room.

[0169] Implementation process and decision-making: Case 1: Decision on the identification method for "Meeting Room B": S51: The matching departments are {Strategic Investment Department, Board Office}, with a quantity of 2. 2 < 5, and 2 = 2 (equal to the preset value), which theoretically allows for quick confirmation. However, for demonstration purposes, we assume we are proceeding to S52.

[0170] S52: Both departments have more than 5 matching meeting rooms, and there are no affected departments. Proceed to S53.

[0171] S53 Preliminary Data: The percentage of meeting rooms that cannot be used as targets for management optimization in the two departments are: 85% for the Strategic Investment Department and 90% for the Board Office. This means that more than 75% of their matched meeting rooms are in a "low-competition" environment under management.

[0172] S531: Since the proportions of both departments are greater than the threshold of 0.75, the condition is met. Therefore, the "Strategic Discussion Room" is identified using the method of "identifying it as a basic meeting room for management optimization." Because both departments possess a large number of "low-competition" resources, removing the control over "Meeting Room B" simply turns it into a free competition point, which has a negligible impact on the overall high availability of both departments, but can increase opportunities for other departments.

[0173] Case 2: Decision on the identification method for "Meeting Room C": S51: Matching departments are {Product Department, Marketing Department, Quality Department}, quantity is 3. 3 < 5, and 3 > 2, proceed to S52.

[0174] S52: All three departments have more than 3 matching meeting rooms, and no departments are affected. Proceed to S53.

[0175] S53 Pre-load Data: The product department's "non-optimizable" ratio is 40% (meaning that 60% of the matching meeting rooms are already in free competition, and the selection of departments has adapted to high competition).

[0176] The "non-optimizable" proportion of the marketing department is 80% (highly controlled, low-competition department).

[0177] The "non-optimizable" percentage in the Quality Department is 30% (screening department, highly competitive environment).

[0178] S531: The proportion of the marketing department (80% > 75%) does not meet the requirements, but the product department (40% < 75%) and the quality department (30% < 75%) do not meet the requirements, so proceed to S532.

[0179] S532: The selected departments are those with a proportion not exceeding 75%, namely the Product Department (40%) and the Quality Department (30%). If a selected department exists among the matching departments for Meeting Room "Meeting Room C", proceed to S533.

[0180] S533: Calculate the control demand factor (Example formula: Factor = (Number of departments screened / Total number of matching departments) * (1 / Average non-optimizable proportion of screened departments)).

[0181] The proportion of departments selected is approximately 2 / 3 ≈ 0.667.

[0182] The average non-optimizable percentage of the screening departments (Product Department, Quality Department) = (40% + 30%) / 2 = 35% = 0.35.

[0183] The control demand factor is approximately 1.905 (0.667 / 0.35). The final decision is that factor 1.905 > threshold 1.8. Therefore, the "Project Review Room" is identified as "unsuitable as a control optimization target."

[0184] The Product and Quality departments are already "screening departments," with only about 35% of their matching meeting rooms remaining in a controlled "low-competition" environment (a key guarantee of their availability). The "Project Debriefing Room" is one such example. If control were lifted, these two departments would lose a valuable "low-competition" location, forced to compete for this newly opened space in an already competitive environment with 60-70% availability, potentially causing a significant drop in overall usability. To protect the survival of departments already at a competitive disadvantage, control over "Meeting Room C" must be maintained.

[0185] The identification-based decision-making method constructed in this embodiment realizes a profound shift in resource management thinking from "managing physical resources" to "managing the competitive ecosystem." Its core value lies in two aspects: First, it systematically quantifies the value of "control," recognizing that control not only restricts use but also shapes a differentiated competitive environment. Second, it accurately predicts the varying impacts of policy changes (de-control) on different market participants (departments), preventing potential collateral damage from a "one-size-fits-all" reform.

[0186] Example 2 Secondly, such as Figure 5 As shown, the present invention provides a logistics service management system, which employs the above-described logistics service management method, specifically including: The control method determination module, the control processing module, and the identification processing module are all included. The control method determination module is responsible for determining the control and processing method for the conference room. The control and management processing module is responsible for determining whether it is necessary to identify and process the control and management optimization objectives in the conference room; The identification and processing module is responsible for determining the identification and processing method for the conference room as a management and control optimization target.

[0187] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the embodiments of apparatus, devices, and non-volatile computer storage media are basically similar to the method embodiments, so the descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0188] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0189] The above description is merely one or more embodiments of this specification and is not intended to limit this specification. Various modifications and variations can be made to the one or more embodiments of this specification by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of one or more embodiments of this specification should be included within the scope of the claims of this specification.

Claims

1. A logistics service management method, characterized in that, Specifically, it includes: Based on meeting room booking data, the availability of meeting rooms on different dates is determined, and the management and control methods for the meeting rooms are determined by combining the matching of available meeting rooms with the meeting needs of different departments. Based on the department's meeting booking data, determine the stability type of the department's meeting needs profile. Based on different stability types of profiles, the department's meeting room usage data and management methods, determine the booking and management of meeting rooms on different dates. Based on the management and usage data of meeting rooms on different dates, when it is determined that the management and optimization targets in the meeting rooms need to be identified and processed, proceed to the next step. Determine the degree of demand matching of the meeting room in different departments, and determine the identification and processing method of the meeting room as a management optimization target by combining the demand matching of different departments with meeting rooms that cannot be used as management optimization targets.

2. The logistics service management method as described in claim 1, characterized in that, The meeting room reservation data is determined based on the meeting rooms booked on different dates.

3. The logistics service management method as described in claim 1, characterized in that, The availability of the meeting rooms is determined based on the dates on which the meeting rooms are not booked.

4. The logistics service management method as described in claim 1, characterized in that, The method for determining the management and control methods for the conference room is as follows: Determine the number of available meeting rooms on different dates based on the availability of meeting rooms on different dates; Based on the matching situation of available meeting rooms with the meeting needs of different departments, the matching departments for the available meeting rooms are determined; Based on the number of available meeting rooms on different dates and the matching departments of the available meeting rooms, the management and control methods for the meeting rooms are determined.

5. The logistics service management method as described in claim 4, characterized in that, The matching department for the vacant meeting room is determined based on the number of times the vacant meeting room is used in that department. Specifically, departments with a usage frequency greater than a preset usage frequency threshold are selected as the matching departments.

6. The logistics service management method as described in claim 1, characterized in that, The meeting needs profiles for the aforementioned departments can be categorized into stable needs profiles, general stable needs profiles, and change profiles.

7. The logistics service management method as described in claim 1, characterized in that, The stability type of the department's meeting needs profile is determined based on the number of times different meeting rooms meet the department's meeting needs, specifically including: The demand matching coefficient of the meeting room is determined based on the proportion of the number of times the meeting room meets the meeting needs of the department in the total number of meeting needs of the department. If the department has a meeting room with a demand matching coefficient greater than a preset matching coefficient threshold, then the meeting demand profile of the department is determined to be a stable demand profile. If the department does not have a meeting room with a demand matching coefficient greater than a preset matching coefficient threshold, obtain the maximum value of the demand matching coefficient of different meeting rooms, and determine whether the maximum value of the demand matching coefficient of the meeting room is less than the preset matching coefficient value. If yes, determine that the stable type of the meeting demand profile of the department is a variable profile; otherwise, determine that the stable type of the meeting demand profile of the department is a general stable profile.

8. The logistics service management method as described in claim 1, characterized in that, The method for determining the reserved and controlled meeting room is as follows: Using different profile stability types, the number of times the meeting room is used in the department within the most recent preset time period is determined from the meeting room usage data of the department, and the departments with usage deviations are determined based on the number of times they are used. Based on the degree of matching between the meeting room and the usage needs of the department with usage deviation, it is determined that the meeting room belongs to the department with usage deviation and matching meeting room usage. Based on the fact that the meeting room belongs to a department with usage deviations from matching meeting rooms, and the stable profile type of the department with usage deviations, and in conjunction with the control processing method, the reserved control meeting room in the meeting room is determined.

9. The logistics service management method as described in claim 1, characterized in that, The method for determining the meeting room as the target for management and control optimization is as follows: Based on the degree of matching between the needs of different departments, the departments to which the meeting room belongs are determined, and the departments to which the meeting room belongs are designated as matching departments. Determine the number of matching meeting rooms used by the matching department, and use the number of matching meeting rooms used to identify meeting rooms that cannot be used as management optimization targets; Based on the matching department of the meeting room, and the data of meeting rooms that cannot be used as management optimization targets in the matching meeting rooms of different matching departments, a method for identifying and processing the meeting room as a management optimization target is determined.

10. A logistics service management system, employing the logistics service management method according to any one of claims 1-9, characterized in that, Specifically, it includes: The control method determination module, the control processing module, and the identification processing module are all included. The control method determination module is responsible for determining the control and processing method for the conference room. The control and management processing module is responsible for determining whether it is necessary to identify and process the control and management optimization objectives in the conference room; The identification and processing module is responsible for determining the identification and processing method for the conference room as a management and control optimization target.

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