WO2024034161A1

WO2024034161A1 - Information management system and information management method

Info

Publication number: WO2024034161A1
Application number: PCT/JP2023/005727
Authority: WO
Inventors: 耀介秋下; アンジャリラジト; 壮希櫻井; 浩二浦脇; 光博木谷; 浩資大島
Original assignee: 株式会社日立製作所
Priority date: 2022-08-10
Filing date: 2023-02-17
Publication date: 2024-02-15
Also published as: JP2024025056A

Abstract

The present invention: extracts assets available to a shipper from usage status data indicating the usage status of one or a plurality of asset owners' assets used to deliver packages using electric vehicles (EVs), on the basis of the usage status data and the delivery specifications of packages to be delivered by the shipper; reads, from evaluation data for evaluating asset owners and assets owned by the asset owners, evaluation indicators of the asset owners of the extracted available assets with respect to concerns emphasized by the shipper when planning the operation of assets; reads, from policy data that specifies an asset owner evaluation policy for each shipper, a score threshold value for the evaluation indicators as defined according to the weights of the evaluation indicators; extracts asset owners satisfying the read score threshold value from extracted usage status data; and outputs an operation plan for the assets to be used by the shipper, on the basis of asset data indicating the status of the assets owned by the extracted asset owners.

Description

Information management system and information management method

The present invention relates to an information management system and an information management method.

Vehicle management devices and information processing devices have been proposed to plan operation while taking into consideration the status of EV (Electric Vehicle) vehicles. The device described in Patent Document 1 highly accurately plans vehicle operations for multiple districts according to the deterioration state of the EV vehicle's battery and external fluctuation factors such as seasonal information and weather information regarding multiple districts. do. In addition, the device described in Patent Document 2 collects infrastructure information in real time, calculates evaluation values regarding multiple evaluation indicators based on the collected information, compares the individual evaluation values, and determines priorities, etc. Perform operational planning according to parameters.

JP2021-86570A Japanese Patent Application Publication No. 2016-149168

In recent years, in the logistics business, EV vehicles have been increasingly introduced in order to realize low-carbon logistics as an effort to achieve SDGs (Sustainable Development Goals). However, business formats in which logistics companies (shippers) own assets such as EV vehicles and EV stations that serve as their charging equipment are costly due to issues such as maintenance and EV vehicle battery life issues. Therefore, attention is being focused on business formats (4PL: 4th party logistics) in which shippers utilize multiple businesses that own assets (asset owners). In this type of business, it is necessary to aggregate multiple asset owners and real-time asset status and plan asset operations for multiple shippers. In addition, in order to realize low-carbon logistics, asset owners who contribute to energy conservation may be prioritized, or asset owners whose drivers are overworked may be avoided because they are considered to be at high risk of accidents. Each shipper needs to plan operations while taking various interests into account; however, considering actual operations, it is desirable to set interests simply.

Conventionally, for commercial EV vehicles, there is a known technology for making operational plans that take into consideration vehicle conditions, charging time, location of charging stations, etc. In Patent Document 1, a highly accurate vehicle deployment plan is generated by considering the influence of external fluctuation factors such as the season and environment and the deterioration state of the battery of the EV vehicle on the travel distance and travel time of the vehicle. However, when adopting a business structure such as 4PL, information regarding asset owners is not taken into account, and the above technology is insufficient for operational planning.

In addition, information processing technology related to the operation of social infrastructure is known as a technology that expands the scope of operation planning. In Patent Document 2, information on multiple infrastructures is collected in real time, evaluation values regarding multiple evaluation indicators are calculated based on the collected information, individual evaluation values are compared, and operation planning is performed according to parameters such as priority. . Therefore, it is considered possible to replace this with technology that evaluates multiple asset owners in a 4PL business format using multiple evaluation indicators. However, EV operation plans require evaluations that take into account various concerns that differ from many shippers, and in consideration of actual operation, it is desirable that the settings be simple. Therefore, it is conceivable to evaluate multiple concerns by grouping them into categories such as ESG scores (E:Environmental, S:Social, G:Governance), but in Patent Document 2, "operation according to parameters such as priority" is considered. It does not include the means to determine the plan, and operation becomes complicated when there are many evaluation indicators. Furthermore, in the EV operation plan, even if the evaluation value of the asset owner is high, if the asset is hardly used, it cannot be included in the operation plan. On the other hand, in order to carry out operations, it is necessary to perform a relative evaluation within the range of assets that can be planned based on the current asset usage situation, and dynamically determine the acceptable range for the shipper. The above technology does not describe how to take real-time situations into consideration when calculating an operation plan, and is insufficient for operation planning.

In view of the above points, the present invention provides an information management system and method for planning optimal asset management while taking into consideration asset utilization status and various concerns of shippers for multiple asset owners in a simple procedure. The purpose is to provide

An information management system according to the present invention is an information management system that uses a computer having a processor and a memory to support the construction of an operation plan regarding delivery of packages, and the processor is configured to deliver packages using an EV (Electric Vehicle). Based on the usage data indicating the usage status of assets of one or more asset owners and the delivery specifications of the package to be delivered by the shipper, the assets available to the shipper are The asset owner of the available asset extracted from the data and evaluation data for evaluating the assets owned by the asset owner and the asset owner is important to the shipper in planning the operation of the asset. read out an evaluation index for the interest to be viewed, and read out a score threshold for the evaluation index, which is determined according to the weight of the evaluation index, from policy data that defines an evaluation policy for asset owners for each shipper; The asset owner who satisfies the score threshold is extracted from the extracted usage status data, and the shipper uses the asset based on the asset data indicating the status of the asset owned by the extracted asset owner. The information management system is configured to output an operation plan for the assets.

According to the present invention, it is possible to plan optimal asset management while taking into account the usage status of the asset and considering the various interests of shippers with respect to multiple asset owners using a simple procedure.

3 is a flowchart of an information management method according to the present embodiment. FIG. 1 is a configuration diagram of an information management system according to the present embodiment. 1 is a schematic diagram of a computer according to the present embodiment. FIG. 3 is an example of an explanatory diagram of a policy storage unit according to the present embodiment. FIG. 3 is an example of an explanatory diagram of an asset usage status storage unit according to the present embodiment. FIG. 3 is an example of an explanatory diagram of an asset collection data storage unit according to the present embodiment. It is an example of an explanatory diagram of a score storage part concerning a present example. FIG. 3 is an example of an explanatory diagram of an evaluation data storage unit according to the present embodiment. It is an example of an explanatory diagram of a score history storage part concerning a present example. It is an example of the block diagram of the policy update part based on a present Example. It is an example of the block diagram of the asset extraction part based on a present Example. It is an example of the block diagram of the score evaluation part based on a present Example. It is an example of the block diagram of the score standard recommendation part based on a present Example. It is an example of the block diagram of the improvement estimation part based on a present Example. It is a flowchart of improvement estimation in the information management method based on a present Example. This is an example of a screen output for recommending score standards and setting thresholds according to the present embodiment. This is an example of a screen output for estimating the ESG score improvement pattern and the expected number of orders based on the ESG score improvement pattern according to the present example. FIG. 2 is a diagram illustrating an example in which the information management system according to the present embodiment is applied to a logistics business.

Hereinafter, embodiments of the present invention will be described with reference to the drawings. The following description and drawings are examples for explaining the present invention, and are omitted and simplified as appropriate for clarity of explanation. The present invention can also be implemented in various other forms. Unless specifically limited, each component may be singular or plural.

The position, size, shape, range, etc. of each component shown in the drawings may not represent the actual position, size, shape, range, etc. in order to facilitate understanding of the invention. Therefore, the present invention is not necessarily limited to the position, size, shape, range, etc. disclosed in the drawings.

In the following description, various information may be explained using expressions such as "database", "table", and "list", but various information may be expressed using data structures other than these. "XX table", "XX list", etc. are sometimes referred to as "XX information" to indicate that they do not depend on the data structure. When describing identification information, when expressions such as "identification information", "identifier", "name", "ID", and "number" are used, they can be replaced with each other.

If there are multiple components having the same or similar functions, the same reference numerals may be given different suffixes for explanation. However, if there is no need to distinguish between these multiple components, the subscripts may be omitted in the description.

In addition, in the following explanation, processing performed by executing a program may be explained, but the program is executed by a processor (e.g., CPU, GPU (Graphics Processing Unit)) to perform predetermined processing. Since the processing is performed using storage resources (for example, memory) and/or interface devices (for example, communication ports) as appropriate, the main body of the processing may be a processor. Similarly, the subject of processing performed by executing a program may be a controller, device, system, computer, or node having a processor. The main body of processing performed by executing a program may be an arithmetic unit, and may include a dedicated circuit (for example, FPGA (Field-Programmable Gate Array) or ASIC (Application Specific Integrated Circuit)) that performs specific processing. .

A program may be installed on a device such as a computer from a program source. The program source may be, for example, a program distribution server or a computer-readable storage medium. When the program source is a program distribution server, the program distribution server includes a processor and a storage resource for storing the program to be distributed, and the processor of the program distribution server may distribute the program to be distributed to other computers. Furthermore, in the following description, two or more programs may be realized as one program, or one program may be realized as two or more programs.

Hereinafter, embodiments of the present invention will be explained in detail based on the drawings.

FIG. 2A shows an information management system when the present invention is applied to a logistics business. The information management system 21 in FIG. 2A includes an access control device 22, an operation planning device 23, a score evaluation device 24, and a storage device 25. The access control device 22 includes an asset usage status extraction section 201, a policy update section 202, and an asset extraction section 203. The operation planning device 23 includes an operation specification input section 204, an operation planning section 205, and an operation plan input/output section 206. The score evaluation device 24 includes an evaluation data input section 207, an asset data collection section 208, a score evaluation section 209, an evaluation index weight input section 210, a threshold input section 211, a score standard recommendation section 212, and an improvement estimation section 213. The storage device 25 includes a policy storage section D201, an asset usage status storage section D202, an asset collection data storage section D203, a score storage section D204, an evaluation data storage section D205, and a score history storage section D206.

The access control device 22, operation planning device 23, and score evaluation device 24 included in the information management system 21 include, for example, a CPU 9202, a memory 9203, an HDD (Hard Disk Drive), etc., as shown in FIG. 2B (computer schematic diagram). an external storage device 9204, an external media output device 9207 that reads and writes information to and from a portable storage medium such as a CD (Compact Disk) or USB memory, an input device 9206 such as a keyboard or mouse, and a display, etc. This can be realized by a general computer 9201 equipped with an output device 9205 and a network communication device 9208 such as a NIC (Network Interface Card) for connecting to a communication network N. In FIG. 2A, an external storage device 9204 is connected to each device as the storage device 25 via a communication network.

Further, various data stored in this system or used for processing can be realized by the CPU 9202 reading out and using the data from the memory 9203 or the external storage device 9204. In addition, each functional unit of this system (for example, asset usage extraction unit 201, policy update unit 202, asset extraction unit 203, operation specification input unit 204, operation planning unit 205, operation plan input/output unit 206, evaluation data Input unit 207, asset data collection unit 208, score evaluation unit 209, evaluation index weight input unit 210, threshold input unit 211, score standard recommendation unit 212, improvement estimation unit 213) This can be achieved by loading a predetermined program into the memory 9203 and executing it.

The above-mentioned predetermined program is stored (downloaded) in the external storage device 9204 from the storage medium via the external media output device 9207 or from the network via the network communication device 9208, and then loaded onto the memory 9203. It may also be executed by the CPU 9202. Alternatively, the program may be directly loaded onto the memory 9203 from a storage medium via the external media output device 9207 or from a network via the network communication device 9208, and executed by the CPU 9202.

A series of processing procedures for performing an operation plan will be explained with reference to FIG.

FIG. 1 is an example of a flowchart showing the processing procedure in the information management system shown in FIGS. 2 to 17. The operation based on this flowchart is shown below.

Step 101: The score evaluation device 24 starts this process at a predetermined timing.

Step 102: The score evaluation device 24 determines whether the weight of the evaluation index is set by the evaluation index weight input unit 210, and if the weight is not set, the process proceeds to step 103 (step 102; NO), and the evaluation index If the weight has already been set, the process advances to step 104 (step 102; YES).

Step 103: The score evaluation device 24 causes the evaluation index weight input unit 210 to input evaluation index weights regarding various concerns for asset owners that the shipper considers important in operational planning, and updates the policy of the access control device 22. The unit 202 stores the asset owner evaluation policy in the policy storage unit D201 (FIG. 3). Details of the process will be described later with reference to FIG. Assets are resources used to deliver packages using EVs, and include EVs, charging stations, and various other hardware and software resources. Asset owners are business owners such as companies and organizations that own, maintain and manage these assets.

Step 104: The score evaluation device 24 causes the threshold value input unit 211 to input the threshold value of the ESG score related to the asset owner in the operation plan, and the policy update unit 202 of the access control device 22 uses the policy storage unit as a policy for asset data extraction. Store in D201 (Figure 3). Details of the process will be described later with reference to FIG.

Step 105: The operation planning device 23 causes the operation specification input unit 204 to input specifications related to the shipper's delivery.

Step 106: The access control device 22 uses the asset usage status extraction unit 201 to extract the usage status of the asset from the asset usage status storage unit D202, and extracts the asset owner who owns the usable asset (FIG. 4). Details of the process will be described later with reference to FIG.

Step 107: The score evaluation device 24 uses the score evaluation unit 209 to calculate the weight of the evaluation index inputted in step 103 among the asset owners extracted in step 106, and the score is stored in the evaluation data storage unit D205. An ESG score is calculated using the numerical value of the evaluation index and stored in the score storage unit D204 (FIGS. 6 and 7). Details of the processing will be described later with reference to FIGS. 10 and 11.

Step 108: The access control device 203 uses the asset extraction unit 203 to extract an asset owner whose ESG score satisfies the threshold based on the ESG score calculated in step 107 and the threshold input in step 104. Details of the process will be described later with reference to FIG.

Step 109: The operation planning unit 205 of the operation planning device 23 performs an asset operation plan among the asset owners who satisfy the threshold extracted in step 108. In addition, the operation plan input/output unit 205 outputs the asset operation plan, allows the shipper to decide on the operation plan, and stores the asset usage status from the determined content in the asset usage status storage unit D202. Details of the process will be described later with reference to FIG.

Step 110: The operation planning device 23 causes the operation specification input unit 204 to input whether all delivery specifications have been met, and determines whether or not it has been completed. If not completed, return to step 105 (step 110; NO); if completed, end (step 110; YES, step 111).

The information management system in FIG. 2 is realized with a configuration as shown in the example below.

The evaluation index weight input unit 210 inputs the weight of the evaluation index according to the shipper's interests. The weight of the evaluation index may be input each time, or it is not necessary to input it each time if it has been input once.

The threshold input section 211 inputs the ESG score threshold that the asset owner should satisfy when making an operation plan.

The policy update unit 202 updates the weight and threshold of the evaluation index.

FIG. 9 is an example of a configuration diagram of the policy update unit according to this embodiment. The policy update unit 202 includes an evaluation index weight update unit 901 and a threshold update unit 902.

The evaluation index weight updating unit 901 stores the weight of the evaluation index input by the evaluation index weight input unit 210 in the policy storage unit D201. The threshold update unit 902 stores the ESG score threshold input by the threshold input unit 211 in the policy storage unit D201.

FIG. 3 is an example of an explanatory diagram of the policy storage unit according to this embodiment. As shown in FIG. 3, the weight of the evaluation index and each threshold value of the ESG score are stored for each shipper, depending on the concern for the asset owner. The above concerns are various concerns for asset owners that shippers consider important when planning operations, such as the environment (E:Environmental), society (S:Social), and corporate governance (G:Governance). , is a perspective that shippers believe is important for the long-term growth of companies in order to realize a sustainable society. A score based on this perspective (ESG score) allows quantitative measurement and relative comparison of the performance and risk of the asset owner, which is the company being evaluated. For example, when evaluating the ESG score E based on the asset's power consumption and the carbon dioxide emissions of the asset owner's facilities, the shipper AA may calculate the asset's power consumption by calculating the asset's power consumption from the carbon dioxide emissions of the asset owner's facilities. If you also place importance on E, store the weight as 0.7 for power consumption and 0.3 for carbon dioxide emissions so that the total weight for E is 1. Furthermore, since each ESG score has a different degree of importance, each ESG score is input as a value between 0 and 1, and this is stored as a threshold value. In this example, the ESG score thresholds for shipper AA are 0.91 for E, 0.7 for S, and 0.8 for G, respectively.

In the operational specification input section 204, delivery specifications such as the weight of the package to be delivered and the collection/delivery destination are input.

The asset usage status extraction unit 201 extracts asset owners who can use the asset from the asset usage status storage unit D202. To extract asset owners who can use assets, it is possible to extract asset owners who can secure the amount of assets based on the minimum amount of assets required for the operation plan empirically from the asset usage status, or to extract the asset owners who can secure the amount of assets based on the minimum amount of assets required for the operation plan, or The minimum required amount of assets may be determined using a regression model using delivery specifications such as as explanatory variables, and asset owners who can secure the amount of assets may be extracted. Note that the regression model may be created for each shipper. Furthermore, if the amount of assets that can be secured by a certain asset owner is insufficient for the minimum required amount of assets, a combination of multiple asset owners may be treated as a new asset owner. In this case, the numerical value of the evaluation index stored in the score storage unit D204, which will be described later, is a value calculated using the asset amount as a weight.

FIG. 4 is an example of an explanatory diagram of the asset usage status storage unit according to this embodiment. As shown in FIG. 4, for each asset owner, information is stored that indicates the number of assets owned and usage status, such as currently in use, reserved status, and expected usage status. For example, Company A has 1000 EV vehicles (autonomous driving), but the assets in use are 800, the reserved assets are 500, and the assets expected to be used in the future are stored as 600. In addition, the expected usage can be determined by calculating the expected number of usage for several days and weeks in the future by the average value of the number of usage for the past few days and weeks, or by calculating the expected number of usage for several days and weeks in the future, or by calculating the expected number of usage for several days and weeks in the future. A predictive model may be constructed and derived from the data. When building a predictive model, the predictive model is incorporated into the asset data collection unit 208. Regarding the construction of a prediction model, there are many known and well-known techniques such as machine learning related to time-series prediction, so please refer to the respective textbooks.

Note that the asset data collection unit 208 collects information related to all assets connected to the information management system in real time, and stores the collected information in the asset usage status storage unit D202 and the asset collection data storage unit D203.

FIG. 5 is an example of an explanatory diagram of the asset collection data storage unit according to this embodiment. As shown in Figure 5, for each asset, information such as the asset owner name, asset name, battery status and remaining battery power, driving area, usage status, and user information are stored for each asset. There is. This information is used for operation planning in the operation planning section 205.

FIG. 6 is an example of an explanatory diagram of the score storage unit according to this embodiment. As shown in Figure 6, the numerical value of the evaluation index is stored as a value between 0 and 1 for each asset owner, and the evaluation is based on the ESG score evaluated by all asset owners and the evaluation index weight of each shipper. The ESG score obtained will be stored. In this example, for asset owner Company A, the numerical values of evaluation indicators such as power consumption (E), carbon dioxide emissions (E), working hours (S), ..., and asset owner code of conduct (G) are as follows. It shows that it was calculated as "0.4", "0.8", "0.9", and "0.8". In addition, for asset owner Company A, the ESG score evaluated by all asset owners is calculated as "0.6", "0.7", and "0.7", respectively, and the ESG score evaluated by each shipper's evaluation index weight is: For example, if the shipper is AA Company, it shows that the calculations were "0.52", "0.7", and "0.7". In addition, for the ESG score evaluated by all asset owners, it is possible to use evaluation index weights that are divided equally, or it is also possible to use evaluation index weights that are set empirically based on the tendencies that each shipper places importance on.

The score evaluation unit 209 normalizes the numerical value of each evaluation index and calculates an ESG score based on the weight of the evaluation index.

FIG. 11 is an example of a configuration diagram of the score evaluation section according to this embodiment. The score evaluation section 209 includes an evaluation data extraction section 1101, an E score calculation section 1102, an S score calculation section 1103, and a G score calculation section 1104.

The evaluation data extraction unit 1101 starts extracting evaluation data from the evaluation data storage unit D205 in response to data input from the evaluation data input unit 207. Further, the evaluation data extraction unit 1101 starts extraction by the policy extraction unit 1002 in addition to data input by the evaluation data input unit 207. When the policy extraction unit 1002 starts extraction, evaluation data is extracted from among the asset owners received from the policy extraction unit 1002.

The E-score calculation unit 1102 calculates an E-score that aggregates evaluation indicators related to the environment, and stores it in the score storage unit D204. Furthermore, when the E-score calculation is evaluated by all asset owners, the score is also stored in the score history storage unit D206. E-scores are calculated by normalizing the evaluation index values, and when evaluating all asset owners, use equally divided evaluation index weights, or use an evaluation set empirically based on the trends that each shipper places importance on. Calculated by weighted average using index weights. Alternatively, when the policy extraction unit 1102 starts extraction, the policy extraction unit 1102 calculates a weighted average using evaluation index weights.

The S score calculation unit 1103 calculates an S score that aggregates evaluation indicators related to social, and stores it in the score storage unit D204. Furthermore, when the S score is evaluated by all asset owners, the score is also stored in the score history storage unit D206. Similar to the E-score calculation unit 1102, the evaluation index is aggregated by normalizing the numerical value of the evaluation index and then calculating the weighted average.

The G-score calculation unit 1104 calculates a G-score that aggregates evaluation indicators related to corporate governance, and stores it in the score storage unit D204. Furthermore, when the G-score calculation is evaluated by all asset owners, the score is also stored in the score history storage unit D206. Similar to the E-score calculation unit 1102, the evaluation index is aggregated by normalizing the numerical value of the evaluation index and then calculating the weighted average.

FIG. 7 is an example of an explanatory diagram of the evaluation data storage unit according to this embodiment. As shown in Figure 7, each asset owner is provided with information related to the asset such as EV vehicle power consumption, carbon dioxide emissions, average overtime hours, and the number of violations of regulations such as traffic rules. Stores information related to. The data stored in the evaluation data storage unit D205 is stored when registering an asset owner in this system. In Figure 7, for example, Company A has EV vehicle power consumption of 7 [km/kwh], carbon dioxide emissions of 20 [kg-CO2e/m2/number of assets], average overtime of 30 hours, and annual code violations of 30. Indicates ownership of the asset.

FIG. 8 is an example of an explanatory diagram of the score history storage unit according to this embodiment. As shown in Figure 8, ESG scores and number of orders are stored for each asset owner on a one-year basis. ESG scores store the values evaluated by all asset owners, and are rarely changed significantly over a period of days or weeks, so they are stored on a yearly basis, but they are also stored on a yearly basis. You may do so. In Figure 8, for example, Company A's ESG scores in fiscal 2022 were "0.5," "0.7," and "0.7," and the number of orders for assets (for example, charging stations) was "100,000." It shows. The number of ordered assets is, for example, set in another system such as a sales system managed by the asset owner, or calculated from the number of "in use" assets stored in the asset usage status storage unit D202.

The asset extraction unit 203 narrows down the asset owners according to the shipper's threshold.

FIG. 10 is an example of a configuration diagram of the asset extraction unit according to this embodiment. The asset extraction unit 203 includes a data request unit 1001, a policy extraction unit 1002, and a policy matching unit 1003.

The data request unit 1001 requests extraction of available assets and policy when the shipper's delivery specifications are input by the operational specification input unit 204.

The policy extraction unit 1002 extracts from the policy storage unit D201 the evaluation index weight and threshold value related to the shipper whose delivery specifications have been input by the data request unit 1001. Furthermore, it requests the score evaluation unit 209 to evaluate the ESG scores among the asset owners extracted by the asset usage status extraction unit 201.

The policy matching unit 1003 compares the threshold value extracted by the policy extraction unit 1002 with the ESG score extracted from the score storage unit D204, and extracts asset owners with ESG scores equal to or higher than the threshold value.

The operation planning unit 205 implements an asset operation plan for the narrowed down asset owners, outputs the results to the operation plan input/output unit 206, and outputs the results of asset usage according to the determined operation plan to the asset usage status storage unit D202. Store. In the operation plan, for example, when operating an EV vehicle, the asset with ID Asset-A-EVA1 is excluded from the operation target because it is in use, and the asset with ID Asset-A-EVA2 is excluded from the operation target because it is in use. However, the asset with the ID Asset-Z-EV500, which is excluded because the battery condition is not good and is not suitable for long-distance driving, is not in use and the battery level is 80%. It is possible to make an operational plan such as operating the battery because it is sufficient and the battery condition is good. Various optimization methods can be used in operational planning. For example, it is possible to set multiple objectives such as battery deterioration status and power consumption based on conditions such as the delivery destination included in the delivery specifications, and to optimize the evolution. There are many well-known optimization techniques, such as deriving a Pareto solution using an algorithm, so please refer to the respective textbooks.

FIG. 12 is an example of a configuration diagram of the score standard recommendation section according to this embodiment. The score standard recommendation section 212 includes an E score standard calculation section 1201, an S score standard calculation section 1202, a G score standard calculation section 1203, and a standard score standard calculation section 1204.

The E-score standard calculation unit 1201 calculates a threshold standard value for the E-score that aggregates evaluation indicators related to the environment so that the operation plan can be implemented. In order to implement an operation plan, you can empirically calculate a reference value that can secure the amount of assets based on the minimum amount of assets required for the operation plan, or you can use regression using delivery specifications such as package amount as an explanatory variable. The minimum required amount of assets may be determined using a model, and a reference value may be calculated to ensure that amount of assets. Note that the regression model may be created for each shipper.

The S score standard calculation unit 1202 uses the same method as the E score standard calculation unit 1201 to calculate a threshold standard value for the S score, which aggregates evaluation indicators related to social, so that the operation plan can be implemented.

The G-score standard calculation unit 1203 calculates a threshold standard value for the G-score that aggregates evaluation indicators related to corporate governance, using the same method as the E-score standard calculation unit 1201, so that the operation plan can be implemented. .

In order to consider all scores, the standard score criteria calculation unit 1204 standardizes the E, S, and G scores, and uses the same method as the E score criteria calculation unit 1201 to calculate the score that is the sum of the standardized scores. Calculate the standard value of the threshold so that the plan can be implemented. Each calculated reference value becomes a reference value in the threshold input section 211.

FIG. 15 is a diagram showing an example of a screen displayed by the threshold value input section 211 of this embodiment. As shown in FIG. 15, the threshold value input unit 211 can receive threshold settings for each of the E, S, and G scores from the user. In addition, the threshold input unit 211 is configured to calculate the inverse of the E, S, and G scores, with the vertical axis representing the percentage of asset owners who satisfy the score relative to all asset owners, and the horizontal axis representing the E, S, and G scores. Display cumulative distribution. The user can check the number of corresponding asset owners based on the set threshold. For example, when the threshold value input unit 211 receives a slide operation in the vertical direction of buttons (

buttons

1501, 1502, 1503) for setting the threshold values for each score of E, S, and G, the threshold value input unit 211 The positions of the

reference lines

1504, 1505, and 1506 displayed in association with the threshold values are moved in conjunction with the slide operation. At this time, the threshold input unit 211 displays the proportion (number of people) of asset owners corresponding to the positions of the moved

reference lines

1504, 1505, and 1506. This example shows that the asset owners who satisfy the threshold are α, β, and γ, respectively. In this way, the threshold input unit 211 outputs asset owners (Y people) who satisfy the threshold value from among all the asset owners (XXX people) according to the threshold value. Furthermore, by selecting a radio button, the reference value calculated by the score reference recommendation unit 212 can be set as the threshold value for each score of E, S, and G.

Next, a series of processing steps for inputting asset data and estimating improvements based on the input, which are executed in the information management system of this embodiment configured as above, will be described with reference to the flowchart in FIG. 14. The operation based on this flowchart is shown below.

Step 1401: The score evaluation device 24 starts this process at a predetermined timing.

Step 1402: The score evaluation device 24 causes the evaluation data input unit 207 to input information regarding the asset owner and the asset (FIG. 7), and stores it in the evaluation data storage unit D205.

Step 1403: The score evaluation device 24 uses the score evaluation unit 209 to calculate the ESG score and stores it in the score storage unit D204 (FIG. 11).

Step 1404: The score evaluation device 24 uses the improvement estimate 213 to estimate the number of orders expected for the asset owner due to the improvement of the ESG score, and outputs the content. Details of the process will be described later with reference to FIG.

The evaluation data input unit 207 inputs evaluation data related to assets and asset owners provided by asset owners, and stores the information in the evaluation data storage unit D205.

The improvement estimation unit 213 extracts ESG score improvement patterns, estimates the number of orders for each improvement pattern, and outputs the results.

FIG. 13 is an example of a configuration diagram of the improvement estimation section according to this embodiment. The improvement estimation unit 213 includes an ESG score improvement pattern calculation unit 1301, an order quantity estimation unit 1302, and an improvement estimate output unit 1303.

The ESG score improvement pattern calculation unit 1301 calculates an ESG score improvement pattern from the ESG score calculated by the score evaluation unit 209 and the ESG score transition history stored in the score history storage unit D206. In calculating the improvement pattern, if multiple other asset owners have had ESG scores in the past that are close to a certain level or higher than the ESG scores calculated by the score evaluation unit 209, and their ESG scores have improved. Then, the ESG score after improvement is calculated by referring to the amount of change in that ESG score. Note that in calculating the improvement pattern, a plurality of improvement patterns may be prepared in advance, and a plurality of ESG scores after improvement may be calculated from the current evaluation value of the asset owner.

The number of orders estimated unit 1302 estimates the number of orders expected based on the improved ESG score calculated by the ESG score improvement pattern calculation unit 1301 and the number of orders expected based on the current ESG score. In estimating the number of orders, the ESG score improvement pattern calculation unit 1301 uses the number of orders received by the asset owner and the asset amount thereof, which is the reference source for the ESG score transition amount, and the asset owner's assets that are the subject of this estimation. Estimate the number of orders based on the quantity. At this time, you may create a regression model using the amount of ESG score transition, the number of orders received, and the amount of assets as explanatory variables, or you can create a regression model using the amount of ESG score transition, the number of orders received, and the amount of assets as explanatory variables. It may be calculated by adding up the amount and the ratio of the asset amount of the asset owner who is the target of this estimate.

The improvement estimate output unit 1303 outputs the ESG score after improvement calculated by the ESG score improvement pattern calculation unit 1301 and the number of orders calculated by the order quantity estimation unit 1302 as an improvement pattern.

FIG. 16 is a diagram showing an example of a screen displayed by the improvement estimation unit 213 of this embodiment. As shown in FIG. 16, using the ESG score after improvement calculated by the ESG score improvement pattern calculation unit 1301 and the number of orders calculated by the order quantity estimation unit 1302, the current ESG score and the ESG score at the time of multiple improvements are calculated. Display the expected number of orders in a graph. In FIG. 16, for example, the improvement estimating unit 213 displays on the screen a graph 1601 showing the current number of orders received and a graph 1602 showing the number of orders received after estimation, calculated by the order number estimating unit 1302. Furthermore, upon receiving the selection of each of the

graphs

1601 and 1602 from the user, the improvement estimation unit 213 displays the ESG score corresponding to each graph. In FIG. 16, an ESG score 1603 corresponding to the above graph 1601 and an ESG score 1604 corresponding to the above graph 1602 are displayed. The improvement estimation unit 213 outputs the ESG score 1604 in a manner that allows the difference from the current ESG score to be visually recognized. In this example, it can be seen that the differences e, f, and g between the current ESG score value and the estimated ESG score value are displayed.

FIG. 17 is a diagram illustrating an example in which the information management system according to this embodiment is applied to a logistics business. As shown in FIG. 17, the information management system 21 is a system used by multiple shippers and multiple asset owners, and is realized on the cloud 1707. Also, although

shippers

1701, 1702, and 1703 are shown as examples of shippers, they may include many more shippers, and

asset owners

1704, 1705, and 1706 are shown as examples of asset owners, but even more shippers may be included. May also include asset owners.

As described above with reference to the drawings, the information management system in this embodiment is an information management system 21 that supports the construction of an operation plan regarding package delivery using a computer having a processor and a memory. The processor stores usage data (data in the asset usage status storage unit D202) indicating the usage status of one or more asset owners' assets, which is used to deliver the luggage by EV, and the usage status data used to deliver the luggage by the shipper. Based on the specifications (data input from the operational specification input unit 204), assets that can be used by the shipper are extracted from the usage data, and assets owned by the asset owner and the asset owner are evaluated. For the asset owners of the above-mentioned available assets extracted from the evaluation data (data in the evaluation data storage D205) for the purpose of , EV vehicle power consumption, carbon dioxide emissions, average overtime hours), and set the score threshold for the above evaluation indicators determined according to the weight of the above evaluation indicators, and set the asset owner evaluation policy for each shipper. The asset owner who satisfies the threshold value of the read score is extracted from the extracted usage situation data, and the asset owned by the extracted asset owner is read from the policy data (data in policy storage D201). Based on the asset data (data in the asset collection data storage unit D203) indicating the state of the asset, an operation plan for the asset used by the shipper is output. Therefore, in the EV operation plan, it is possible to calculate evaluation indicators for multiple asset owners while taking into account the usage status of assets such as EV, narrow down assets based on the evaluation indicators, and implement the operation plan among the narrowed down assets. It becomes like this. In other words, in order to enable shippers to easily plan EV operation plans by taking into account various concerns of asset owners such as EVs, evaluations concerning multiple asset owners are conducted while taking into account the usage status of the assets. It is possible to calculate indicators, narrow down assets based on the evaluation indicators, and implement operational plans within the narrowed down range.

Furthermore, as described using FIG. 11 and the like, the processor calculates the score for the evaluation index based on the evaluation index read from the evaluation data and the weight of the evaluation index. As a result, even if the weight of the evaluation index that the shipper considers to be important changes due to changes in the business, it is possible to calculate the score for the asset owner in accordance with the change.

Further, as explained using FIGS. 13, 16, etc., the processor stores a score history that associates the calculated score for the evaluation index with the number of orders for the asset for a predetermined period for a plurality of asset owners. data (data in the score history storage unit D206), and among the accumulated score history data, among the asset owners whose score is close to a certain degree to the score for the above evaluation index of the asset owner who is the target of estimation, The amount of change in the score is calculated from the transition history of the score for the above evaluation indicators for asset owners whose number of orders for assets is improving, and the calculated amount of change in the above score and the asset owner who is the target of the estimate are calculated. The number of orders for the above asset that will improve for the asset owner who is the target of the estimate, based on the score for the above evaluation index of Estimate. Thereby, the asset owner to be estimated can estimate the number of orders for his own asset while referring to the scores of other asset owners whose scores are similar to a certain degree.

Further, as explained using FIGS. 12, 15, etc., the processor sets the threshold value of the score based on the calculated score for the evaluation index and the asset owner required for the operation plan of the asset. A reference value (a value obtained from the inverse cumulative distribution) is calculated, and the calculated reference value is set as the threshold of the score. This allows the shipper to confirm the number of asset owners that satisfies the desired score and then set the score threshold.

Note that the present invention is not limited to the above-described embodiments, and includes various modifications. For example, the embodiments described above are described in detail to explain the present invention in an easy-to-understand manner, and the present invention is not necessarily limited to having all the configurations described. Furthermore, it is possible to replace a part of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment to the configuration of one embodiment. Further, it is possible to add, delete, or replace a part of the configuration of each embodiment with other configurations. Further, each of the above-mentioned configurations, functions, processing units, processing means, etc. may be partially or entirely realized in hardware by designing, for example, an integrated circuit. Furthermore, each of the above configurations, functions, etc. may be realized by software by a processor interpreting and executing a program for realizing each function. Information such as programs, tables, files, etc. that realize each function can be stored in memory, a recording device such as a hard disk, an SSD (Solid State Drive), or a recording medium such as an IC card, SD card, or DVD.

201 Asset usage extraction section, 202 Policy update section, 203 Asset extraction section, 204 Operation specification input section, 205 Operation planning section, 206 Operation plan input/output section, 207 Evaluation data input section, 208 Asset data collection section, 209 Score evaluation section, 210 evaluation index weight input section, 211 threshold input section, 212 score standard recommendation section, 213 improvement estimation section, D201 policy storage section, D202 asset usage status storage section, D203 asset collection data storage section, D204 score storage section, D205 evaluation data storage, D206 score history storage

Claims

An information management system that uses a computer having a processor and memory to support the construction of an operation plan regarding delivery of packages,
The processor includes:
Based on the usage status data indicating the usage status of assets of one or more asset owners used to deliver packages by EV (Electric Vehicle) and the delivery specifications of the packages to be delivered by the consignor, the consignor extracting available assets from the usage data;
Concerning the asset owner of the available asset extracted from the assets owned by the asset owner and evaluation data for evaluating the asset owner, concerns that the shipper considers important when planning the operation of the asset; Read out the evaluation index of
reading out a score threshold for the evaluation index, which is determined according to the weight of the evaluation index, from policy data that defines an evaluation policy for asset owners for each shipper;
Extracting asset owners who meet the read score threshold from the extracted usage situation data,
outputting an operation plan for the asset to be used by the shipper based on the extracted asset data indicating the state of the asset owned by the asset owner;
An information management system characterized by:
The processor includes:
calculating a score for the evaluation index based on the evaluation index read from the evaluation data and the weight of the evaluation index;
The information management system according to claim 1, characterized in that:
The processor includes:
Accumulating score history data for a plurality of asset owners, which correlates the calculated score for the evaluation index with the number of orders received for the asset over a predetermined period;
Among the accumulated score history data, among the asset owners whose score is close to a certain degree to the score for the evaluation index of the asset owner who is the target of estimation, the number of orders received for the asset is improving. Calculating the amount of transition of the score from the transition history of the score with respect to the evaluation index,
Based on the calculated transition amount of the score, the score for the evaluation index for the asset owner to be estimated, and the number of orders for the asset for the asset owner whose number of orders for the asset is improving, estimating the number of orders for the asset to be improved for the asset owner to be estimated;
The information management system according to claim 2, characterized in that:
The processor includes:
Calculating a reference value for the threshold of the score based on the calculated score for the evaluation index and the asset owner required for the operation plan of the asset;
setting the calculated reference value as a threshold for the score;
The information management system according to claim 2, characterized in that:
An information management method performed in an information management system that supports the construction of an operation plan regarding package delivery using a computer having a processor and a memory, the method comprising:
Assets that can be used by the shipper based on usage status data indicating the usage status of assets of one or more asset owners used to deliver the baggage by EV and the delivery specifications of the baggage to be delivered by the shipper. is extracted from the usage data,
Concerning the asset owner of the available asset extracted from the assets owned by the asset owner and evaluation data for evaluating the asset owner, concerns that the shipper considers important when planning the operation of the asset; Read out the evaluation index of
reading out a score threshold for the evaluation index, which is determined according to the weight of the evaluation index, from policy data that defines an evaluation policy for asset owners for each shipper;
Extracting asset owners who meet the read score threshold from the extracted usage situation data,
outputting an operation plan for the asset to be used by the shipper based on the extracted asset data indicating the state of the asset owned by the asset owner;
An information management method characterized by:
calculating a score for the evaluation index based on the evaluation index read from the evaluation data and the weight of the evaluation index;
The information management method according to claim 5, characterized in that:
Accumulating score history data for a plurality of asset owners, which correlates the calculated score for the evaluation index with the number of orders received for the asset over a predetermined period;
Among the accumulated score history data, among the asset owners whose score is close to a certain degree to the score for the evaluation index of the asset owner who is the target of estimation, the number of orders received for the asset is improving. Calculating the amount of transition of the score from the transition history of the score with respect to the evaluation index,
Based on the calculated transition amount of the score, the score for the evaluation index for the asset owner to be estimated, and the number of orders for the asset for the asset owner whose number of orders for the asset is improving, estimating the number of orders for the asset to be improved for the asset owner to be estimated;
The information management method according to claim 6, characterized in that:
Calculating a reference value for the threshold of the score based on the calculated score for the evaluation index and the asset owner required for the operation plan of the asset;
setting the calculated reference value as a threshold for the score;
The information management method according to claim 6, characterized in that: