Information management system and information management method

Abstract

To provide an information management system and method that plan optimum asset operation while taking various matter of interest that a consignor has about a plurality of asset owners into consideration as well as use states of assets through a simple procedure.SOLUTION: A method comprises: extracting an asset that a consignor can use based upon use state data on one or more asset owners used to deliver loads and delivery specifications of the loads that the consignor delivers; reading evaluation indexes that the consignor attaches importance to in operation planning of assets as to the owners of the extracted usable assets from evaluation data on the assets that the asset owners own and the asset owners; reading a threshold of scores for the evaluation indexes which is determined according to the weight of evaluation indexes from policy data in which an evaluation policy of an asset owner is determined; extracting an asset owner which satisfies the read threshold of scores; and outputting an operation plan for assets based upon asset data that the extracted asset owner owns.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to an information management system and an information management method. [Background technology]

[0002] Vehicle management devices and information processing devices have been proposed for making operation plans while taking into account the state of EVs (Electric Vehicles) and the like. The device described in Patent Document 1 makes highly accurate plans for vehicle operations in multiple areas according to the deterioration state of the EV vehicle's batteries and external variable factors such as seasonal information and weather information for the multiple areas. The device described in Patent Document 2 collects infrastructure information in real time, calculates evaluation values ​​for multiple evaluation indexes based on the collected information, compares the individual evaluation values, and makes operation plans according to parameters such as priority. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent Publication No. 2021-86570 [Patent Document 2] JP 2016-149168 A Summary of the Invention [Problem to be solved by the invention]

[0004] In recent years, the introduction of electric vehicles has been progressing in the logistics business to realize low-carbon logistics as an effort to achieve the SDGs (Sustainable Development Goals). However, a business model in which logistics companies (shippers) own assets such as EV vehicles and EV stations that serve as charging facilities is costly due to issues such as maintenance and the battery life of EV vehicles. Therefore, a business model in which shippers utilize multiple companies (asset owners) that own assets (4PL: 4th party logistics) is attracting attention. In such a business model, it is necessary to aggregate the status of multiple asset owners and real-time assets and make asset operation plans for multiple shippers. In addition, in order to realize low-carbon logistics, each shipper needs to make operation plans while taking into account various concerns, such as giving priority to asset owners who contribute to energy conservation, or avoiding the use of asset owners whose drivers are overworked because they are considered to be at high risk of causing accidents. However, when considering actual operations, it is desirable to set the concerns simply.

[0005] Conventionally, there is known a technology for making an operation plan for commercial EV vehicles that considers the vehicle condition, 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 variable factors such as season and environment and the deterioration state of the battery of the EV vehicle on the vehicle's travel distance and travel time. However, in the case of a business form such as 4PL, information on the asset owner is not considered, and the above technology is insufficient for the operation plan.

[0006] In addition, information processing technology related to the operation of social infrastructure is known as a technology that expands the target area of ​​operation planning. In Patent Document 2, information on multiple infrastructures is collected in real time, evaluation values ​​for multiple evaluation indexes are calculated based on the collected information, the individual evaluation values ​​are compared, and operation planning is performed according to parameters such as priority. Therefore, it is considered possible to replace it with a technology that evaluates multiple asset owners who have a 4PL business form with multiple evaluation indexes. However, in EV operation planning, it is necessary to evaluate taking into account various concerns that differ depending on a large number of shippers, and in consideration of actual operation, it is desirable to set it simply. Therefore, it is possible to evaluate multiple concerns by categorizing them like ESG scores (E: Environmental, S: Social, G: Governance), but Patent Document 2 states "calculation of operation plan according to parameters such as priority," but does not include a means for determining it, and operation becomes complicated when there are many evaluation indexes. In addition, in EV operation planning, even if the evaluation value of an asset owner is high, if the asset is almost in use, it cannot be included in the operation plan. On the other hand, in order to operate the system, it is necessary to relatively evaluate the range of assets that can be used for operation planning under the current asset usage situation and dynamically determine the acceptable range for the shipper.The above technology does not describe how to take into account the real-time situation in the calculation of the operation plan, and is insufficient for operation planning.

[0007] In view of the above, the present invention aims to provide an information management system and method for planning optimal asset management while taking into account the usage status of assets and considering various concerns of shippers regarding multiple asset owners in a simple manner. [Means for solving the problem]

[0008] The information management system according to the present invention is an information management system that supports the creation of an operation plan for the delivery of goods by a computer having a processor and a memory, wherein the processor is configured as an information management system characterized in that it extracts assets available to a shipper from usage status data indicating the usage status of assets of one or more asset owners used to deliver goods by EVs (Electric Vehicles) and delivery specifications of goods delivered by the shipper, reads evaluation indexes regarding concerns that the shipper considers important when planning the operation of the assets for the asset owners of the extracted available assets from evaluation data for evaluating the assets owned by the asset owners and the asset owners, reads score thresholds for the evaluation indexes determined according to the weights of the evaluation indexes from policy data that defines evaluation policies for asset owners for each shipper, extracts asset owners who satisfy the read score thresholds from the extracted usage status data, and outputs an operation plan for the assets used by the shipper based on the extracted asset data indicating the status of the assets owned by the asset owners. Effect of the Invention

[0009] According to the present invention, it is possible to plan optimal asset management while taking into account the asset usage status and various concerns of shippers regarding multiple asset owners in a simple manner. [Brief description of the drawings]

[0010] [Figure 1] 1 is a flowchart of an information management method according to an embodiment of the present invention. [Figure 2A] FIG. 1 is a configuration diagram of an information management system according to an embodiment of the present invention. [Figure 2B] FIG. 1 is a schematic diagram of a computer according to an embodiment of the present invention. [Diagram 3] FIG. 4 is an explanatory diagram of a policy storage unit according to the embodiment; [Figure 4]FIG. 2 is an example of an explanatory diagram of an asset usage status storage unit according to the embodiment; [Diagram 5] FIG. 2 is an example of an explanatory diagram of an asset collection data storage unit according to the present embodiment. [Figure 6] FIG. 4 is an explanatory diagram of a score storage unit according to the embodiment; [Figure 7] FIG. 4 is an explanatory diagram of an example of an evaluation data storage unit according to the present embodiment. [Figure 8] FIG. 4 is an example of an explanatory diagram of a score history storage unit according to the present embodiment. [Figure 9] FIG. 2 is a diagram illustrating an example of a configuration of a policy update unit according to the embodiment; [Figure 10] FIG. 2 is a diagram illustrating an example of a configuration of an asset extraction unit according to the present embodiment. [Figure 11] FIG. 2 is a diagram illustrating an example of a configuration of a score evaluation unit according to the present embodiment. [Figure 12] FIG. 4 is a diagram illustrating an example of a configuration of a score criterion recommendation unit according to the present embodiment. [Figure 13] FIG. 2 is a diagram illustrating an example of a configuration of an improvement estimation unit according to the present embodiment. [Figure 14] 11 is a flowchart of improvement estimation in the information management method according to the present embodiment. [Figure 15] 13 is an example of a screen output for recommending score criteria and setting thresholds according to an embodiment of the invention. [Figure 16] 13 is an example of a screen output estimating an improvement pattern of an ESG score and the number of orders expected as a result of the improvement pattern according to the present embodiment. [Figure 17] FIG. 1 is a diagram illustrating an example in which an information management system according to an embodiment of the present invention is applied to a logistics business. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] Hereinafter, an embodiment 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 appropriate omissions and simplifications have been made for clarity of explanation. The present invention can be implemented in various other forms. Unless otherwise specified, each component may be singular or plural.

[0012] In order to facilitate understanding of the invention, the position, size, shape, range, etc. of each component shown in the drawings may not represent the actual position, size, shape, range, etc. Therefore, the present invention is not necessarily limited to the position, size, shape, range, etc. disclosed in the drawings.

[0013] In the following explanation, various information may be described using expressions such as "database," "table," and "list," but the various information may be expressed in other data structures. To indicate independence of data structure, "XX table," "XX list," and the like may be referred to as "XX information." When describing identification information, when expressions such as "identification information," "identifier," "name," "ID," and "number" are used, these are interchangeable.

[0014] When there are multiple components having the same or similar functions, they may be described by using the same reference numerals with different subscripts. However, when there is no need to distinguish between these multiple components, the subscripts may be omitted.

[0015] In addition, in the following description, processing performed by executing a program may be described, but the program is executed by a processor (e.g., a CPU, a Graphics Processing Unit (GPU)) to perform a defined process using storage resources (e.g., a memory) and / or an interface device (e.g., a communication port) as appropriate, so the subject of the processing may be the processor. Similarly, the subject of the processing performed by executing a program may be a controller, device, system, computer, or node having a processor. The subject of the processing performed by executing a program may be a calculation unit, and may include a dedicated circuit (e.g., a Field-Programmable Gate Array (FPGA) or an Application Specific Integrated Circuit (ASIC)) that performs a specific process.

[0016] A program may be installed in 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 may include a processor and a storage resource for storing a program to be distributed, and the processor of the program distribution server may distribute the program to be distributed to other computers. In the following description, two or more programs may be realized as one program, and one program may be realized as two or more programs.

[0017] Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings.

[0018] FIG. 2A shows an information management system in the case where 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 unit 201, a policy update unit 202, and an asset extraction unit 203. The operation planning device 23 includes an operation specification input unit 204, an operation plan unit 205, and an operation plan input / output unit 206. The score evaluation device 24 includes an evaluation data input unit 207, an asset data collection unit 208, a score evaluation unit 209, an evaluation index weight input unit 210, a threshold input unit 211, a score criterion recommendation unit 212, and an improvement estimation unit 213. The storage device 25 includes a policy storage unit D201, an asset usage status storage unit D202, an asset collection data storage unit D203, a score storage unit D204, an evaluation data storage unit D205, and a score history storage unit D206.

[0019] The access control device 22, the operation planning device 23, and the score evaluation device 24 of the information management system 21 can be realized by a general computer 9201 including a CPU 9202, a memory 9203, an external storage device 9204 such as a hard disk drive (HDD), an external medium output device 9207 for reading and writing information from and to a portable storage medium such as a compact disk (CD) or a USB memory, an input device 9206 such as a keyboard or a mouse, an output device 9205 such as a display, and a network communication device 9208 such as a network interface card (NIC) for connecting to a communication network N, as shown in FIG. 2A. In FIG. 2A, the external storage device 9204 is connected to each device as a storage device 25 via a communication network.

[0020] Moreover, various data stored in this system or used for processing can be realized by the CPU 9202 reading and using it from the memory 9203 or the external storage device 9204. Moreover, each functional unit of this system (for example, the asset usage status extraction unit 201, the policy update unit 202, the asset extraction unit 203, the operation specification input unit 204, the operation plan unit 205, the operation plan input / output unit 206, the evaluation data input unit 207, the asset data collection unit 208, the score evaluation unit 209, the evaluation index weight input unit 210, the threshold input unit 211, the score criterion recommendation unit 212, and the improvement estimation unit 213) can be realized by the CPU 9202 loading a predetermined program stored in the external storage device 9204 into the memory 9203 and executing it.

[0021] The above-mentioned predetermined program may be stored (downloaded) into the external storage device 9204 from a storage medium via the external medium output device 9207 or from a network via the network communication device 9208, and then loaded onto the memory 9203 and executed by the CPU 9202. Alternatively, the program may be directly loaded onto the memory 9203 from a storage medium via the external medium output device 9207 or from a network via the network communication device 9208, and executed by the CPU 9202.

[0022] A series of processing steps for making an operation plan will be described with reference to FIG.

[0023] Fig. 1 is an example of a flowchart showing a processing procedure in the information management system shown in Figs. 2 to 17. The operation based on this flowchart will be described below.

[0024] Step 101: The score evaluation device 24 starts this process at a predetermined timing.

[0025] Step 102: The score evaluation device 24 determines whether or not the weight of the evaluation index has been set using the evaluation index weight input unit 210. If the weight of the evaluation index has not been set, the process proceeds to step 103 (step 102; NO), and if the weight of the evaluation index has already been set, the process proceeds to step 104 (step 102; YES).

[0026] Step 103: The score evaluation device 24 causes the evaluation index weight input unit 210 to input the weights of evaluation indexes for various concerns about asset owners that the shipper considers important in planning operations, and the policy update unit 202 of the access control device 22 stores the weights in the policy storage unit D201 as a policy for asset owner evaluation (FIG. 3). Details of the process will be described later with reference to FIG. 9. Assets are resources used to deliver packages by EVs, and include various hardware resources such as EVs and charging stations, and software resources. Asset owners are business owners such as companies and organizations that own and maintain these assets.

[0027] Step 104: The score evaluation device 24 causes the threshold input unit 211 to input a threshold value for the ESG score related to the asset owner for the management plan, and stores the threshold value in the policy storage unit D201 as a policy for asset data extraction by the policy update unit 202 of the access control device 22 (FIG. 3). Details of the process will be described later with reference to FIG.

[0028] Step 105: The operation planning device 23 causes the operation specification input unit 204 to input specifications related to delivery from the shipper.

[0029] Step 106: The access control device 22 extracts the asset usage status from the asset usage status storage unit D202 by the asset usage status extraction unit 201, and extracts the asset owners who own the available assets (FIG. 4). The details of the process will be described later with reference to FIG.

[0030] Step 107: The score evaluation device 24 calculates an ESG score for the asset owners extracted in step 106 using the numerical values ​​of the evaluation indexes stored in the evaluation data storage unit D205 based on the weights of the evaluation indexes input in step 103, by the score evaluation unit 209, and stores the score in the score storage unit D204 (FIGS. 6 and 7). Details of the process will be described later with reference to FIGS. 10 and 11.

[0031] Step 108: The access control device 203 extracts asset owners having ESG scores that satisfy the threshold based on the ESG scores calculated in step 107 and the threshold input in step 104, using the asset extraction unit 203. Details of the process will be described later with reference to FIG.

[0032] Step 109: The operation planning device 23, through the operation planning unit 205, performs an asset operation plan among the asset owners who satisfy the threshold value extracted in step 108. In addition, the operation plan input / output unit 205 outputs the asset operation plan, has the shipper decide on the operation plan, and stores the asset usage status in the asset usage status storage unit D202 based on the decided content. Details of the process will be described later with reference to FIG.

[0033] Step 110: The operation planning device 23 judges whether or not all delivery specifications have been met by inputting whether or not all delivery specifications have been met through the operation specification input unit 204. If not, the process returns to step 105 (step 110; NO), and if completed, the process ends (step 110; YES, step 111).

[0034] The information management system of FIG. 2 is realized by the configuration shown below as an example.

[0035] The weight of the evaluation index is input according to the shipper's interest in the evaluation index weight input section 210. The weight of the evaluation index may be input every time, or it does not have to be input every time once it has been input.

[0036] The threshold input unit 211 inputs the ESG score threshold that the asset owner must meet when planning an investment.

[0037] The policy update unit 202 updates the weights and thresholds of the evaluation indexes.

[0038] 9 is a diagram showing an example of the configuration of the policy update unit according to the present embodiment. The policy update unit 202 includes an evaluation index weight update unit 901 and a threshold update unit 902.

[0039] The evaluation index weight update unit 901 stores the weights of the evaluation indexes input by the evaluation index weight input unit 210 in the policy storage unit D201. The threshold update unit 902 stores the thresholds of the ESG scores input by the threshold input unit 211 in the policy storage unit D201.

[0040] FIG. 3 is an example of an explanatory diagram of the policy storage unit according to the present embodiment. As shown in FIG. 3, for each shipper, the weight of the evaluation index and each threshold value of the ESG score are stored according to the concerns of the asset owner. The above concerns are various concerns of the asset owner that the shipper considers important in the operation plan, such as the environment (E), society (S), and corporate governance (G), which are perspectives that the shipper considers important for the long-term growth of the company in order to realize a sustainable society. The score based on the perspective (ESG score) can quantitatively measure and relatively compare the performance and risk of the asset owner, which is the evaluated company. For example, when the ESG score E is evaluated based on the power consumption of the asset and the carbon dioxide emission related to the facility of the asset owner, if the shipper AA company considers the power consumption of the asset more important than the carbon dioxide emission related to the facility of the asset owner, the weight of the power consumption is stored as 0.7 and the weight of the carbon dioxide emission is stored as 0.3 so that the sum of the weights on E is 1. In addition, since the importance of each ESG score differs, each ESG score is entered as a value between 0 and 1, and these are stored as thresholds. In this example, the ESG score thresholds for shipper AA are entered as 0.91 for E, 0.7 for S, and 0.8 for G.

[0041] In the operation specification input section 204, delivery specifications such as the weight of the package to be delivered and the collection and delivery destination are input.

[0042] The asset usage status extraction unit 201 extracts asset owners who can use assets from the asset usage status storage unit D202. The asset owners who can use assets may be extracted by extracting asset owners who can secure the minimum asset amount empirically required for the operation plan from the asset usage status, or by determining the minimum required asset amount using a regression model with delivery specifications such as the amount of cargo as explanatory variables, and extracting asset owners who can secure the minimum required asset amount. Note that the regression model may be created for each shipper. Furthermore, if the amount of assets that a certain asset owner can secure is insufficient for the minimum required asset amount, 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 described later is a value calculated with the asset amount as a weight.

[0043] FIG. 4 is an example of an explanatory diagram of the asset usage status storage unit according to the present embodiment. As shown in FIG. 4, for each asset owner, information on the number of assets owned, in use indicating the usage status, reserved indicating the reservation status, and expected usage is stored. For example, for 1000 EV vehicles (self-driving) of company A, 800 assets in use, 500 assets reserved, and 600 assets expected to be used in the future are stored. In addition, whether or not it is expected to be used may be determined by calculating the expected number of uses over the next few days or weeks as the average number of uses over the past few days or weeks, or by constructing a prediction model from time series data of asset usage. When constructing a prediction model, the prediction model is incorporated into the asset data collection unit 208. There are many publicly known and well-known technologies for constructing a prediction model, such as machine learning related to time series prediction, and each textbook should be referred to.

[0044] The asset data collection unit 208 collects information on all assets connected to the information management system in real time, and stores the collected information in an asset usage status storage unit D202 and an asset collected data storage unit D203.

[0045] Fig. 5 is an example of an explanatory diagram of the asset collection data storage unit according to the present embodiment. As shown in Fig. 5, for each asset, the asset owner's name, asset name, battery state and remaining battery power in the case of an EV vehicle, driving area, whether or not the vehicle is being used, user information, etc. are stored. These pieces of information are used for the operation plan in the operation plan unit 205.

[0046] FIG. 6 is an example of an explanatory diagram of the score storage unit according to the present embodiment. As shown in FIG. 6, for each asset owner, the numerical value of the evaluation index is stored as a value between 0 and 1, and the ESG score evaluated by the asset owners as a whole and the ESG score evaluated by the evaluation index weight of each shipper are stored. In this example, for asset owner A company, the numerical values ​​of the evaluation indexes such as power consumption (E), carbon dioxide emissions (E), working hours (S), ..., and the asset owner's code of conduct (G) are calculated as "0.4", "0.8", "0.9", and "0.8", respectively. In addition, for asset owner A company, the ESG scores evaluated by the asset owners as a whole are calculated as "0.6", "0.7", and "0.7", respectively, and the ESG scores evaluated by the evaluation index weight of each shipper are calculated as "0.52", "0.7", and "0.7" when the shipper is AA company, for example. In addition, the ESG score assessed across all asset owners may use equal evaluation index weights, or may use evaluation index weights empirically determined based on the priorities of each shipper.

[0047] 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.

[0048] 11 is a diagram showing an example of the configuration of the score evaluation unit according to this embodiment. The score evaluation unit 209 includes an evaluation data extraction unit 1101, an E score calculation unit 1102, an S score calculation unit 1103, and a G score calculation unit 1104.

[0049] 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. The evaluation data extraction unit 1101 also starts extraction by the policy extraction unit 1002, in addition to data input from the evaluation data input unit 207. When extraction is started by the policy extraction unit 1002, evaluation data is extracted from among the asset owners received from the policy extraction unit 1002.

[0050] The E-score calculation unit 1102 calculates an E-score by aggregating the environmental evaluation indicators, and stores it in the score storage unit D204. When the E-score is calculated to be evaluated across all asset owners, the score is also stored in the score history storage unit D206. The E-score is calculated by normalizing the numerical values ​​of the evaluation indicators, and when the E-score is calculated across all asset owners, the E-score is calculated by a weighted average using equal evaluation index weights, or evaluation index weights that are empirically set based on the tendencies that each shipper places importance on. Alternatively, when extraction is started by the policy extraction unit 1102, the policy extraction unit 1102 calculates a weighted average using the evaluation index weights.

[0051] The S score calculation unit 1103 calculates an S score that aggregates evaluation indicators related to society, and stores it in the score storage unit D204. When the S score is calculated to be evaluated by all asset owners, the score is also stored in the score history storage unit D206. As with the E score calculation unit 1102, the evaluation indicators are aggregated by normalizing the numerical values ​​of the evaluation indicators and then calculating a weighted average.

[0052] The G-score calculation unit 1104 calculates a G-score by aggregating evaluation indicators related to corporate governance, and stores it in the score storage unit D204. When the G-score is calculated to be evaluated across all asset owners, the score is also stored in the score history storage unit D206. As with the E-score calculation unit 1102, the evaluation indicators are aggregated by normalizing the numerical values ​​of the evaluation indicators and then calculating a weighted average.

[0053] FIG. 7 is an example of an explanatory diagram of the evaluation data storage unit according to the present embodiment. As shown in FIG. 7, for each asset owner, information related to the asset, such as EV power consumption, and information related to the asset owner, such as carbon dioxide emissions, average overtime hours, and the number of violations of regulations such as traffic rules, are stored. The data stored in the evaluation data storage unit D205 is stored when the asset owner is registered in the present system. FIG. 7 shows, for example, that Company A is an asset owner with EV power consumption of 7 [km / kwh], carbon dioxide emissions of 20 [kg-CO2e / m2 / number of assets], average overtime hours of 30 hours, and the number of violations of regulations per year of 30 times.

[0054] FIG. 8 is an example of an explanatory diagram of the score history storage unit according to the present embodiment. As shown in FIG. 8, the ESG score and the number of orders are stored for each asset owner on a yearly basis. The ESG score is stored as a value when evaluated by the entire asset owners, and since it rarely fluctuates significantly in a few days or weeks, it is stored in a yearly unit, but it may be stored in a few months or years. In FIG. 8, for example, the ESG scores of Company A in fiscal year 2022 are "0.5", "0.7", and "0.7", respectively, and the number of orders for assets (e.g., charging stations) is "100,000". The number of orders for assets is, for example, set in another system such as a sales system managed by the asset owner, or calculated from the number of assets "in use" stored in the asset usage status storage unit D202.

[0055] The asset extraction unit 203 narrows down the asset owners according to a threshold value of the shippers.

[0056] 10 is a diagram showing an example of the configuration 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.

[0057] When the delivery specifications of the shipper are inputted by the operation specification input unit 204, the data request unit 1001 requests extraction of available assets and policies.

[0058] The policy extraction unit 1002 extracts, from the policy storage unit D201, the evaluation index weights and thresholds related to the shippers who have input the delivery specifications by the data request unit 1001. Furthermore, the score evaluation unit 209 is requested to evaluate the ESG scores of the asset owners extracted by the asset usage status extraction unit 201.

[0059] 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 who have ESG scores equal to or greater than the threshold value.

[0060] The operation plan unit 205 executes the asset operation plan for the narrowed down asset owners, outputs the result to the operation plan input / output unit 206, and stores the result of asset usage according to the determined operation plan in the asset usage status storage unit D202. In the operation plan, for example, in the operation of an EV vehicle, an asset with an ID of Asset-A-EVA1 is excluded from the operation target because it is in use, an asset with an ID of Asset-A-EVA2 is excluded because it is not in use and has a remaining battery of 100% but is not suitable for long-distance driving because its battery condition is not good, and an asset with an ID of Asset-Z-EV500 is operated because it is not in use, has a remaining battery of 80%, which is sufficient, and is in good battery condition. In the operation plan, various optimization methods can be used. For example, multiple objectives such as battery deterioration state and power consumption can be set based on conditions such as the delivery destination included in the delivery specifications, and a Pareto solution can be derived using an evolutionary algorithm. There are many publicly known optimization techniques, and each textbook should be referred to.

[0061] 12 is an example of a configuration diagram of the score criterion recommendation unit according to this embodiment. The score criterion recommendation unit 212 includes an E score criterion calculation unit 1201, an S score criterion calculation unit 1202, a G score criterion calculation unit 1203, and a standard score criterion calculation unit 1204.

[0062] The E-score standard calculation unit 1201 calculates a threshold standard value for the E-score that aggregates the evaluation indexes related to the environment so that the operation plan can be implemented. In order to implement the operation plan, a standard value that can secure the asset amount may be calculated based on the minimum asset amount required for the operation plan empirically, or a regression model that uses delivery specifications such as the amount of cargo as explanatory variables to determine the minimum asset amount required and calculate a standard value that can secure the asset amount. Note that the regression model may be created for each shipper.

[0063] The S-score standard calculation unit 1202 calculates a threshold standard value for the S-score, which is an aggregate of social-related evaluation indexes, in a manner similar to that of the E-score standard calculation unit 1201 so that the operation plan can be implemented.

[0064] The G-score standard calculation unit 1203 calculates a threshold standard value for the G-score, which is an aggregate of evaluation indicators related to corporate governance, in a manner similar to that of the E-score standard calculation unit 1201 so that an operational plan can be implemented.

[0065] In the standard score criterion calculation unit 1204, in order to take all scores into consideration, the scores of E, S, and G are standardized, and the standardized scores are summed up to calculate a threshold reference value so that the operation plan can be implemented in the same manner as in the E score criterion calculation unit 1201. Each calculated reference value becomes the reference value in the threshold input unit 211.

[0066] FIG. 15 is a diagram showing an example of a screen displayed by the threshold input unit 211 of this embodiment. As shown in FIG. 15, the threshold input unit 211 can accept the setting of the threshold for each of the E, S, and G scores from the user. The threshold input unit 211 also displays an inverse cumulative distribution for each of the E, S, and G scores, with the vertical axis representing the ratio of asset owners who satisfy the score to the total number of asset owners, and the horizontal axis representing each of the E, S, and G scores. The user can confirm the number of asset owners corresponding to the set threshold. For example, when the threshold input unit 211 accepts an operation of sliding the buttons (buttons 1501, 1502, and 1503) for setting the threshold for each of the E, S, and G scores from the user in the up and down directions, the threshold input unit 211 moves the positions of the reference lines 1504, 1505, and 1506 displayed in association with the threshold on the inverse cumulative distribution in conjunction with the sliding operation. At this time, the threshold input unit 211 displays the ratio (number of asset owners) corresponding to the positions of the moved reference lines 1504, 1505, and 1506. In this example, the asset owners who satisfy the threshold are α, β, and γ, respectively. The threshold input unit 211 outputs the asset owners (Y) who satisfy the threshold from among all asset owners (XXX) according to the threshold in this way. Furthermore, by selecting a radio button, the standard value calculated by the score standard recommendation unit 212 can be set as the threshold for each of the E, S, and G scores.

[0067] Next, a series of processing steps for inputting asset data and estimating improvement based on the input, which are executed in the information management system of this embodiment configured as described above, will be described with reference to the flowchart of Fig. 14. The operation based on this flowchart will be described below.

[0068] Step 1401: The score evaluation device 24 starts this process at a predetermined timing.

[0069] Step 1402: The score evaluation device 24 causes the evaluation data input unit 207 to input information (FIG. 7) related to the asset owner and the asset, and stores it in the evaluation data storage unit D205.

[0070] Step 1403: The score evaluation device 24 calculates an ESG score by the score evaluation unit 209, and stores the ESG score in the score storage unit D204 (FIG. 11).

[0071] Step 1404: The score evaluation device 24 estimates the number of orders expected for the asset owner due to the improvement of the ESG score, and outputs the details thereof, using the improvement estimation 213. The details of the process will be described later with reference to FIG.

[0072] The evaluation data input unit 207 allows the asset provided by the asset owner and evaluation data relating to the asset owner to be input, and stores the information in the evaluation data storage unit D205.

[0073] The improvement estimation unit 213 extracts improvement patterns of the ESG score, estimates the number of orders for each improvement pattern, and outputs the results.

[0074] 13 is a diagram illustrating an example of the configuration of the improvement estimation unit 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 estimation output unit 1303.

[0075] The ESG score improvement pattern calculation unit 1301 calculates an improvement pattern of the ESG score from the ESG score calculated by the score evaluation unit 209 and the transition history of the ESG score 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 the ESG score calculated by the score evaluation unit 209 to a certain extent or more and the ESG scores have improved, the transition amount of the ESG score is referenced to calculate the improved ESG score. Note that the calculation of the improvement pattern may be performed by preparing multiple improvement patterns in advance and calculating multiple improved ESG scores from the current evaluation value of the asset owner.

[0076] The order number estimation unit 1302 estimates the number of orders expected for the improved ESG score calculated by the ESG score improvement pattern calculation unit 1301 and the number of orders expected for the current ESG score. In estimating the number of orders, the ESG score improvement pattern calculation unit 1301 estimates the number of orders from the number of orders and their asset amount of the asset owner that was the reference source for the transition amount of the ESG score and the asset amount of the asset owner that is the subject of the current estimate. At this time, a regression model may be created with the transition amount of the ESG score, the number of orders, and the asset amount as explanatory variables, or the order number of the asset owner that was the reference source for the transition amount of the ESG score may be multiplied by the ratio of the asset amount and the asset amount of the asset owner that is the subject of the current estimate.

[0077] An improvement estimate output unit 1303 outputs the improved ESG score calculated by the ESG score improvement pattern calculation unit 1301 and the number of orders calculated by the number of orders estimation unit 1302 as an improvement pattern.

[0078] 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, the current ESG score and the number of orders expected for each of the ESG scores at the time of improvement are displayed in a graph using the improved ESG score calculated by the ESG score improvement pattern calculation unit 1301 and the number of orders calculated by the order number estimation unit 1302. In FIG. 16, for example, the improvement estimation unit 213 displays on the screen a graph 1601 showing the current number of orders and a graph 1602 showing the number of orders after the estimate, both calculated by the order number estimation unit 1302. Furthermore, when the improvement estimation unit 213 receives a selection of each of the graphs 1601 and 1602 from the user, it displays the ESG scores corresponding to each graph. In FIG. 16, an ESG score 1603 corresponding to the graph 1601 and an ESG score 1604 corresponding to the graph 1602 are displayed. The improvement estimation unit 213 outputs the ESG score 1604 in a manner in which the difference from the current ESG score can be visually recognized. In this example, you can see that the differences e, f, and g between the current ESG score value and the estimated ESG score value are displayed.

[0079] Fig. 17 is a diagram for explaining an example in which the information management system according to the present 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 a cloud 1707. Although shippers 1701, 1702, and 1703 are shown as examples of shippers, more shippers may be included, and although asset owners 1704, 1705, and 1706 are shown as examples of asset owners, more asset owners may be included.

[0080] As described above with reference to the drawings, the information management system in this embodiment is an information management system 21 that supports the creation of an operation plan for the delivery of parcels by a computer having a processor and a memory, and the processor extracts assets that can be used by the shipper from the usage status data (data in the asset usage status storage unit D202) indicating the usage status of assets of one or more asset owners used to deliver parcels by EVs, based on the delivery specifications of the parcels delivered by the shipper (data input from the operation specification input unit 204), and extracts assets that can be used by the shipper from the usage status data, and from evaluation data (data in the evaluation data storage unit D205) for evaluating the assets owned by the asset owner and the asset owner. For the asset owners of the available assets, evaluation indices (e.g., EV power consumption, carbon dioxide emissions, average overtime hours) regarding matters of concern that the shipper considers important in planning the operation of the assets are read out, and a score threshold for the evaluation indices, determined according to the weight of the evaluation indices, is read out from policy data (data in the policy storage unit D201) that defines the evaluation policy of the asset owners for each shipper, asset owners who satisfy the read score threshold are extracted from the extracted usage status data, and an operation plan for the assets used by the shipper is output based on the extracted asset data (data in the asset collection data storage unit D203) indicating the status of the assets owned by the asset owners. Therefore, it becomes possible to calculate evaluation indices for multiple asset owners while taking into account the usage status of assets such as EVs in the EV operation plan, narrow down the assets based on the evaluation indices, and implement the operation plan within the narrowed down assets. In other words, in order to enable shippers to easily make EV operation plans that take into account various concerns regarding asset owners such as EVs, evaluation indexes for multiple asset owners can be calculated while taking into account the asset usage status, the assets can be narrowed down based on the evaluation indexes, and the operation plan can be implemented within the narrowed down assets.

[0081] 11 and the like, the processor calculates a score for the evaluation index based on the evaluation index read from the evaluation data and the weight of the evaluation index. This makes it possible to calculate a score for the asset owner in accordance with the change even if the weight of the evaluation index that the shipper considers important changes due to a change in the business or the like.

[0082] 13, 16, etc., the processor accumulates score history data (data in the score history storage unit D206) that associates the calculated scores for the evaluation index with the number of orders for the assets for a predetermined period for a plurality of asset owners, calculates a transition amount of the score for the evaluation index for asset owners whose scores are close to a certain degree to the score for the evaluation index for the asset owner to be estimated from the accumulated score history data, and estimates the improved number of orders for the assets for the asset owner to be estimated 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 assets for the asset owners whose orders for the assets are improving. This allows the asset owner to be estimated to estimate the number of orders for his / her own assets while referring to the scores of other asset owners whose scores are close to a certain degree.

[0083] 12, 15, etc., the processor calculates a reference value (a value obtained from an inverse cumulative distribution) of the score threshold based on the calculated score for the evaluation index and the asset owners required for the asset operation plan, and sets the calculated reference value as the score threshold. This allows the shipper to set the score threshold after confirming the number of asset owners that meet the score he or she desires.

[0084] The present invention is not limited to the above-mentioned embodiment, and various modifications are included. For example, the above-mentioned embodiment has been described in detail to easily explain the present invention, and is not necessarily limited to those having all the configurations described. It is also 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. It is also possible to add, delete, or replace a part of the configuration of each embodiment with another configuration. In addition, each of the above-mentioned configurations, functions, processing units, processing means, etc. may be realized by hardware, for example, by designing them as integrated circuits. In addition, each of the above-mentioned configurations, functions, etc. may be realized by software by a processor interpreting and executing a program that realizes each function. Information such as a program, table, file, etc. that realizes each function can be placed in a memory, a recording device such as a hard disk or SSD (Solid State Drive), or a recording medium such as an IC card, SD card, or DVD. [Explanation of symbols]

[0085] 201 asset usage status extraction unit, 202 policy update unit, 203 asset extraction unit, 204 operation specification input unit, 205 operation plan unit, 206 operation plan input / output unit, 207 evaluation data input unit, 208 asset data collection unit, 209 score evaluation unit, 210 evaluation index weight input unit, 211 threshold input unit, 212 score standard recommendation unit, 213 improvement estimation unit, D201 policy storage unit, D202 asset usage status storage unit, D203 asset collection data storage unit, D204 score storage unit, D205 evaluation data storage unit, D206 score history storage unit

Claims

1. An information management system that supports the creation of an operational plan for delivery of parcels by a computer having a processor and a memory, comprising: The processor, Extracting assets available to a shipper from usage status data indicating usage status of assets of one or more asset owners used for delivering cargo by an EV (Electric Vehicle) and delivery specifications of cargo delivered by the shipper; From the assets owned by the asset owner and evaluation data for evaluating the asset owner, for the asset owner of the extracted available assets, an evaluation index is read out regarding a concern that a shipper considers important in planning an operation of the asset; A score threshold for the evaluation index, determined according to the weight of the evaluation index, is read from policy data that defines an evaluation policy of an asset owner for each shipper; extracting asset owners who satisfy the read score threshold value from the extracted usage data; outputting an operation plan for the assets used by the shipper based on the extracted asset data indicating the status of the assets owned by the asset owner; 1. An information management system comprising:

2. The processor, calculating a score for the evaluation index based on the evaluation index read from the evaluation data and the weight of the evaluation index; 2. The information management system according to claim 1,

3. The processor, accumulate score history data for a plurality of asset owners, the score for the calculated evaluation index being associated with the number of orders for the assets during a predetermined period; Calculate a transition amount of the score from a transition history of the score for the evaluation index for an asset owner who has an improvement in the number of orders for the asset among asset owners who have scores close to a certain degree to the score for the evaluation index for the asset owner to be estimated from the accumulated score history data; estimating an improved number of orders for the assets for the asset owner that is the subject of the estimate based on the calculated amount of change in the score, the score for the evaluation index for the asset owner that is the subject of the estimate, and the number of orders for the assets for the asset owner whose number of orders for the assets is improving; 3. The information management system according to claim 2.

4. The processor, Calculating a reference value for a threshold of the score based on the calculated score for the evaluation index and an asset owner required for a management plan for the asset; The calculated reference value is set as a threshold value of the score.

3. The information management system according to claim 2.

5. An information management method carried out in an information management system that supports the creation of an operation plan for delivery of parcels by a computer having a processor and a memory, comprising: Extracting assets available to a shipper from the usage status data based on usage status data indicating usage status of one or more asset owners' assets used to deliver packages by EVs and delivery specifications of packages delivered by the shipper; From the assets owned by the asset owner and evaluation data for evaluating the asset owner, for the asset owner of the extracted available assets, an evaluation index is read out regarding a concern that a shipper considers important in planning an operation of the asset; A score threshold for the evaluation index, determined according to the weight of the evaluation index, is read from policy data that defines an evaluation policy of an asset owner for each shipper; extracting asset owners who satisfy the read score threshold value from the extracted usage data; outputting an operation plan for the assets used by the shipper based on the extracted asset data indicating the status of the assets owned by the asset owner; 23. An information management method comprising:

6. calculating a score for the evaluation index based on the evaluation index read from the evaluation data and the weight of the evaluation index; 6. The information management method according to claim 5,

7. accumulate score history data for a plurality of asset owners, the score for the calculated evaluation index being associated with the number of orders for the assets during a predetermined period; Calculate a transition amount of the score from a transition history of the score for the evaluation index for an asset owner who has an improvement in the number of orders for the asset among asset owners who have scores close to a certain degree to the score for the evaluation index for the asset owner to be estimated from the accumulated score history data; estimating an improved number of orders for the assets for the asset owner that is the subject of the estimate based on the calculated amount of change in the score, the score for the evaluation index for the asset owner that is the subject of the estimate, and the number of orders for the assets for the asset owner whose number of orders for the assets is improving; 7. The information management method according to claim 6,

8. Calculating a reference value for a threshold of the score based on the calculated score for the evaluation index and an asset owner required for a management plan for the asset; The calculated reference value is set as a threshold value of the score.

7. The information management method according to claim 6,

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