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 creating operational plans taking into account the status of electric vehicles (EVs). The device described in Patent Document 1 creates highly accurate plans for vehicle operations in multiple areas based on the deterioration state of the EV's batteries and external variables such as seasonal 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 creates operational plans according to parameters such as priority. [Prior art documents] [Patent documents]

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

[0004] In recent years, the logistics industry has been increasingly adopting electric vehicles (EVs) to achieve low-carbon logistics as part of efforts to achieve the Sustainable Development Goals (SDGs). However, a business model in which logistics companies (shippers) own assets such as EV vehicles and charging stations is costly due to issues such as maintenance and EV battery life. Therefore, a business model in which shippers utilize multiple asset owners (asset owners) (4PL: 4th-party logistics) has been gaining attention. This business model requires the aggregation of multiple asset owners and real-time asset status information, and asset operation plans for multiple shippers. Furthermore, to achieve low-carbon logistics, shippers must consider various concerns when planning operations, such as prioritizing asset owners that contribute to energy conservation, or avoiding asset owners with overworked drivers because they are considered to be at high risk of accidents. However, considering practical operations, it is desirable to simplify the definition of these concerns.

[0005] Conventionally, there is known a technology for creating an operation plan for commercial electric vehicles that takes into account the vehicle's condition, charging time, location of charging stations, etc. Patent Document 1 generates a highly accurate vehicle deployment plan by considering the effects of external variables such as the season and environment, and the deterioration state of the EV vehicle's battery on the vehicle's driving distance and driving time. However, in a business model such as 4PL, information about asset owners is not taken into account, and the above technology is insufficient for operation planning.

[0006] Another technology that broadens the scope of operational planning is information processing technology related to the operation of social infrastructure. Patent Document 2 discloses a method for collecting information from multiple infrastructures in real time, calculating evaluation values ​​for multiple evaluation indicators based on the collected information, comparing the individual evaluation values, and formulating an operational plan based on parameters such as priority. Therefore, it is conceivable to replace this technology with a technology that evaluates multiple asset owners operating in a 4PL business model using multiple evaluation indicators. However, EV operational planning requires evaluation that takes into account the various concerns of numerous shippers, and considering practical operations, it is desirable to simplify the setup. Therefore, it is conceivable to evaluate multiple concerns by categorizing them, such as ESG scores (E: Environmental, S: Social, G: Governance). However, Patent Document 2 only describes "calculating an operation plan based on parameters such as priority," but does not include a means for determining this, making operation cumbersome when there are many evaluation indicators. Furthermore, in EV operational planning, even if an asset owner has a high evaluation value, if that asset is mostly in use, it cannot be included in the operational 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 real-time situations into account when calculating the operation plan, and is therefore 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 asset usage status and considering various concerns of shippers regarding multiple asset owners in a simple manner. [Means for solving the problem]

[0008] The information management system of the present invention is an information management system that uses a computer having a processor and memory to support the creation of an operation plan for the delivery of goods, and is configured as an information management system characterized in that the processor 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 for goods delivered by the shipper, reads evaluation indicators 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 indicators, determined according to the weights of the evaluation indicators, 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. [Effects 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 considering the various concerns of shippers regarding multiple asset owners in a simple procedure. [Brief explanation 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] 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. [Figure 3] FIG. 2 is an explanatory diagram of a policy storage unit according to the embodiment; [Figure 4]FIG. 10 is an explanatory diagram of an asset usage status storage unit according to the present embodiment. [Figure 5] FIG. 2 is an explanatory diagram illustrating an example of an asset collection data storage unit according to the present embodiment. [Figure 6] FIG. 2 is an explanatory diagram of a score storage unit according to the present embodiment; [Figure 7] FIG. 2 is an explanatory diagram of an example of an evaluation data storage unit according to the present embodiment. [Figure 8] FIG. 10 is 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 present 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. 2 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] 10 is a flowchart of an improvement estimate in the information management method according to the present embodiment. [Figure 15] 10 is an example of a screen output for recommending score criteria and setting thresholds according to an embodiment of the present invention. [Figure 16] 10 is an example of a screen output that estimates 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 INVENTION

[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 some omissions and simplifications have been made as appropriate 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 types of information may be described using expressions such as "database," "table," and "list," but the various types of information may also be expressed in data structures other than these. To indicate that the information is not dependent on the data structure, "XX table," "XX list," etc. may be referred to as "XX information." When describing identification information, expressions such as "identification information," "identifier," "name," "ID," and "number" are used, and these are interchangeable.

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

[0015] Furthermore, 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 or a GPU (Graphics Processing Unit)) to perform the specified processing while appropriately using storage resources (e.g., memory) and / or interface devices (e.g., communication ports), and therefore the processor may be the subject of the processing. 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 any computing unit, and may include a dedicated circuit (e.g., an FPGA (Field-Programmable Gate Array) or an ASIC (Application Specific Integrated Circuit)) that performs specific processing.

[0016] 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. If the program source is a program distribution server, the program distribution server may include a processor and storage resources 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. Also, 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] 2A shows an information management system in which 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, operation planning device 23, and score evaluation device 24 of the information management system 21 can be realized by a general computer 9201 including, for example, a CPU 9202, a memory 9203, an external storage device 9204 such as an HDD (Hard Disk Drive), an external medium output device 9207 that reads and writes information from and to a portable storage medium such as a CD (Compact Disk) or 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 an NIC (Network Interface Card) for connecting to a communication network N, as shown in FIG. 2A (schematic diagram of a computer). In FIG. 2A, the external storage device 9204 is connected to each device as a storage device 25 via the communication network.

[0020] Furthermore, various data stored in or used for processing in this system can be realized by the CPU 9202 reading and using it from the memory 9203 or the external storage device 9204. Furthermore, 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 creating an operation plan will be described with reference to FIG.

[0023] 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 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 it 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 has the evaluation index weight input unit 210 input the weights of evaluation indexes for various concerns about asset owners that the shipper considers important when planning operations, and the policy update unit 202 of the access control device 22 stores the weights as asset owner evaluation policies in the policy storage unit D201 (FIG. 3). Details of the process will be described later in FIG. 9. Assets are resources used to deliver packages by EV, and include various hardware resources and software resources such as EVs and charging stations. Asset owners are business owners such as companies and organizations that own and maintain these assets.

[0027] Step 104: The score evaluation device 24 allows 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 as a policy for asset data extraction in the policy storage unit D201 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 relating 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 using the asset usage status extraction unit 201, and extracts asset owners who own available assets (FIG. 4). Details of the process will be described later with reference to FIG. 10.

[0030] Step 107: The score evaluation device 24 calculates an ESG score for each asset owner 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 entered 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: Access Control Device 22 The asset extraction unit 203 extracts asset owners who have ESG scores that satisfy the threshold based on the ESG scores calculated in step 107 and the threshold input in step 104. Details of the process will be described later with reference to FIG. 10.

[0032] Step 109: The operation planning device 23, through the operation planning unit 205, makes an asset operation plan among the asset owners who satisfy the threshold extracted in step 108. 206 The asset operation plan is outputted by the above, the shipper is made to decide on the operation plan, and the asset usage status is stored in the asset usage status storage unit D202 based on the decided content. The details of the process will be described later with reference to FIG.

[0033] Step 110: The operation planning device 23 determines whether all delivery specifications have been met by inputting whether they have been met using 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] Figure 2 A The information management system is realized by the configuration shown in the example below.

[0035] The weight of the evaluation index is input in accordance with the shipper's interest in the evaluation index weight input unit 210. The weight of the evaluation index may be input each time, or once it has been input, it does not need to be input each time.

[0036] The threshold input unit 211 inputs the ESG score threshold that the asset owner must meet in order to formulate a management plan.

[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 this 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 explanatory diagram of an example of the policy storage unit according to this embodiment. As shown in FIG. 3, for each shipper, weights of evaluation indicators and thresholds for ESG scores are stored according to the shipper's concerns regarding the asset owner. The concerns are various concerns regarding the asset owner that the shipper considers important in operational planning, such as environmental (E), social (S), and governance (G), which the shipper considers important for the long-term growth of the company in order to realize a sustainable society. A score based on these perspectives (ESG score) allows quantitative measurement and relative comparison of the performance and risk of the asset owner, the company being evaluated. For example, if the ESG score E is evaluated based on the power consumption of the asset and the carbon dioxide emissions associated with the asset owner's facilities, if shipper AA places more importance on the power consumption of the asset than the carbon dioxide emissions associated with the asset owner's facilities, the weight for power consumption is stored as 0.7 and the weight for carbon dioxide emissions is stored as 0.3, so that the total weight for E is 1. Furthermore, 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 thresholds for the ESG scores of 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 empirically extracting asset owners who can secure the minimum asset amount 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 cargo volume as explanatory variables and extracting asset owners who can secure that amount. Note that a 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 values ​​of the evaluation indexes stored in the score storage unit D204 (described later) are calculated using asset amounts as weights.

[0043] FIG. 4 is an explanatory diagram of an example of an asset usage status storage unit according to this embodiment. As shown in FIG. 4, for each asset owner, information on the number of assets owned, the usage status (in use), the reservation status (reserved), and the expected usage status are stored. For example, for 1,000 EVs (autonomous driving) owned by Company A, 800 assets are in use, 500 assets are reserved, and 600 assets are expected to be used in the future are stored. The expected usage may be determined by averaging the expected usage over the next few days or weeks based on the average usage over the past few days or weeks, or by constructing a prediction model from time-series data on asset usage. To construct a prediction model, the prediction model is incorporated into the asset data collection unit 208. There are many well-known techniques for constructing a prediction model, such as machine learning related to time-series prediction. For more information, please refer to the relevant textbooks.

[0044] The asset data collection unit 208 collects information relating 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 collected data storage unit D203.

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

[0046] FIG. 6 is an example of an explanatory diagram of the score storage unit according to this embodiment. As shown in FIG. 6, for each asset owner, the numerical values ​​of the evaluation indicators are stored as values ​​between 0 and 1. The ESG score evaluated by all asset owners and the ESG score evaluated by each shipper based on the evaluation indicator weights are also stored. In this example, for asset owner A, the numerical values ​​of the evaluation indicators such as power consumption (E), carbon dioxide emissions (E), working hours (S), ..., and asset owner code of conduct (G) are calculated as "0.4," "0.8," "0.9," and "0.8," respectively. Furthermore, for asset owner A, the ESG scores evaluated by all asset owners are calculated as "0.6," "0.7," and "0.7," respectively. The ESG scores evaluated by each shipper based on the evaluation indicator weights are calculated as "0.52," "0.7," and "0.7" for the shipper AA, for example. In addition, for the ESG score assessed across all asset owners, it is possible to use equal weighting of the evaluation indicators, or it is possible to use weighting of the evaluation indicators 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 illustrating 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. In addition to data input from the evaluation data input unit 207, the evaluation data extraction unit 1101 also starts extraction using the policy extraction unit 1002. When extraction is started using the policy extraction unit 1002, evaluation data is extracted from the asset owners received from the policy extraction unit 1002.

[0050] The E-score calculation unit 1102 calculates an E-score that aggregates the environmental evaluation indicators and stores it in the score storage unit D204. When the E-score is calculated to be evaluated by all asset owners, the score is also stored in the score history storage unit D206. When the E-score is calculated to be evaluated by all asset owners, the numerical values ​​of the evaluation indicators are normalized, and when the E-score is calculated, the numerical values ​​of the evaluation indicators are normalized, and when the E-score is calculated by all asset owners, the E-score is calculated by a weighted average using equal evaluation indicator weights or evaluation indicator weights that are empirically set based on the tendencies that each shipper places importance on. Alternatively, the policy extraction unit 1002 If you start the extraction by 1002 The evaluation index weights are used to calculate the weighted average.

[0051] The S score calculation unit 1103 calculates an S score that aggregates evaluation indicators related to society, and stores the S score in the score storage unit D204. When the S score is calculated to evaluate 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 that aggregates evaluation indicators related to corporate governance and stores it in the score storage unit D204. When calculating the G-score to evaluate 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 diagram illustrating an evaluation data storage unit according to this embodiment. As shown in FIG. 7, for each asset owner, information related to the asset, such as electric vehicle power consumption, and information related to the asset owner, such as carbon dioxide emissions, average overtime hours, and the number of violations of traffic rules and other regulations, is stored. The data stored in the evaluation data storage unit D205 is stored when the asset owner is registered in this system. FIG. 7 shows, for example, that Company A is an asset owner with electric vehicle power consumption of 7 [km / kWh], carbon dioxide emissions of 20 [kg-CO2e / m2 / number of assets], average overtime hours of 30 hours, and 30 violations of regulations per year.

[0054] FIG. 8 is an example of an explanatory diagram of the score history storage unit according to this 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 evaluated across all asset owners and rarely fluctuates significantly over a period of a few days or weeks. Therefore, the ESG score is stored on a yearly basis, but it may also be stored on a monthly or annual basis. In FIG. 8, for example, the ESG scores for 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 an asset 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 the 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 input 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 for the shippers who have input delivery specifications using 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 planner 205 implements an asset operation plan for the selected asset owners, outputs the results to the operation plan input / output unit 206, and stores the asset usage results according to the determined operation plan in the asset usage status storage unit D202. For example, in the operation of electric vehicles, an operation plan may be implemented such that an asset with an ID of Asset-A-EVA1 is excluded from operation 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 due to poor battery condition; and an asset with an ID of Asset-Z-EV500 is operated because it is not in use but has a remaining battery of 80%, which is sufficient and has good battery condition. Various optimization techniques can be utilized in operation plans. For example, multiple objectives, such as battery degradation 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. Many well-known optimization techniques are available; please refer to textbooks on each.

[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, which is an aggregate of environmental evaluation indicators, so that the operation plan can be implemented. To implement the operation plan, the standard value may be calculated based on the empirical minimum asset amount required for the operation plan to ensure that amount of asset is secured, or the minimum amount of asset required may be determined using a regression model with delivery specifications such as cargo volume as explanatory variables, and the standard value may be calculated so that that amount of asset is secured. Note that a 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 evaluation indicators, in the same manner as 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 the same manner as the E score standard calculation unit 1201 so that the operational plan can be implemented.

[0065] In order to take all scores into consideration, the standard score criterion calculation unit 1204 standardizes the E, S, and G scores, and calculates threshold reference values ​​for the sum of the standardized scores 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 illustrating an example of a screen displayed by the threshold input unit 211 according to this embodiment. As illustrated in FIG. 15, the threshold input unit 211 can accept threshold settings 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 percentage of asset owners who meet the score relative to all 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, upon accepting a user's sliding operation of buttons (buttons 1501, 1502, and 1503) for setting thresholds for each of the E, S, and G scores in the up or down direction, the threshold input unit 211 moves the positions of reference lines 1504, 1505, and 1506, which are displayed on the inverse cumulative distribution in association with the thresholds, in response to the sliding operation. At this time, the threshold input unit 211 displays the percentage (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 people, respectively. The threshold input unit 211 outputs the asset owners (Y people) who satisfy the threshold from among all asset owners (XXX people) 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 asset data input and improvement estimation 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 in 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) relating 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 using the score evaluation unit 209, and stores the ESG score in the score storage unit D204 (FIG. 11).

[0071] Step 1404: The score evaluator 24 evaluates the improvement estimate Department The number of orders expected for the asset owner due to the improvement of the ESG score is estimated and output by 213. Details of the process will be described later with reference to FIG. 13.

[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 an example of a configuration diagram 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 for 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 previously had ESG scores that are close to or above a certain level to the ESG score calculated by the score evaluation unit 209 and these ESG scores have improved, the amount of transition of these ESG scores is referenced to calculate the improved ESG score. Note that the calculation of the improvement pattern may involve preparing multiple improvement patterns in advance and calculating multiple improved ESG scores from the current evaluation value of the asset owner.

[0076] The order quantity 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 current target of the estimation. At this time, a regression model may be created using the transition amount of the ESG score, the number of orders, and the asset amount as explanatory variables, or the calculation may be performed by multiplying the number of orders from the asset owner that was the reference source for the transition amount of the ESG score by the ratio of that asset amount to the asset amount of the asset owner that is the current target of the estimation.

[0077] The 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 illustrating an example of a screen displayed by the improvement estimation unit 213 of this embodiment. As illustrated in FIG. 16 , a graph is displayed showing the current ESG score and the expected number of orders for each of the ESG scores at multiple improvements, based on the improved ESG score calculated by the ESG score improvement pattern calculation unit 1301 and the order number 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 order number and a graph 1602 showing the estimated order number, both calculated by the order number estimation unit 1302. Furthermore, upon receiving a 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 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 that allows the difference from the current ESG score to be visually recognized. In this example, we can see that the differences e, f, and g between the current ESG score and the estimated ESG score are displayed.

[0079] Fig. 17 is a diagram illustrating an example in which an 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 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 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) that indicates the usage status of assets of one or more asset owners used to deliver parcels by EV and based on delivery specifications of parcels to be 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 extracts assets that can be used by the shipper 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, the system reads evaluation indicators (e.g., EV power consumption, carbon dioxide emissions, average overtime hours) related to the concerns that the shipper considers important when planning the operation of the assets, reads score thresholds for the evaluation indicators determined according to the weights of the evaluation indicators from policy data (data in the policy storage unit D201) that defines the evaluation policies of 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 asset data (data in the asset collection data storage unit D203) that indicates the status of the assets owned by the extracted asset owners. Thus, it becomes possible to calculate evaluation indicators 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 indicators, and implement the operation plan within the narrowed down assets. In other words, in order to enable shippers to easily plan EV operations by taking into account various concerns of asset owners such as EVs, evaluation indicators for multiple asset owners can be calculated while taking into account asset usage, and the assets can be narrowed down based on the evaluation indicators, 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, for a predetermined period, the calculated scores for the evaluation index with the number of orders for the assets for a plurality of asset owners, and 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 of the asset owner to be estimated and whose number of orders for the assets has improved from the transition history of the score for the evaluation index for the asset owners in 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 number of orders for the assets has improved. This allows the asset owner to be estimated to estimate the number of orders for his or 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) for 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 who satisfy the shipper's desired score.

[0084] The present invention is not limited to the above-described embodiments and includes various modifications. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and are not necessarily limited to those including all of the described configurations. Furthermore, part of the configuration of one embodiment can be replaced with the configuration of another embodiment, or the configuration of another embodiment can be added to the configuration of one embodiment. Furthermore, part of the configuration of each embodiment can be added, deleted, or replaced with other configurations. Furthermore, the above-described configurations, functions, processing units, processing means, etc. may be implemented in hardware, in part or in whole, by designing, for example, an integrated circuit. Furthermore, the above-described configurations, functions, etc. may be implemented in software, by a processor interpreting and executing a program that realizes each function. Information such as programs, tables, and files that realize each function can be stored in 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 package delivery using a computer having a processor and a memory, The processor: extracting assets available to a shipper from usage status data indicating usage status of assets of one or more asset owners used to deliver packages by EV (Electric Vehicle) and delivery specifications of packages delivered by the shipper; reads out, for the asset owner of the extracted available assets from the assets owned by the asset owner and evaluation data for evaluating the asset owner, evaluation indicators regarding matters of interest that a shipper considers important when planning an operation of the asset; A score threshold for the evaluation index, which is 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 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; An information management system characterized by:

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, wherein:

3. The processor: Accumulating score history data for a plurality of asset owners, in which the calculated scores for the evaluation indexes are associated with the number of orders for the assets over a predetermined period; Among the accumulated score history data, among asset owners whose scores are close to a certain degree to the score for the evaluation index of the asset owner to be estimated, calculate the amount of transition of the score from the score transition history for the evaluation index of asset owners whose number of orders for the assets is improving; estimate the improved number of orders for the assets for the asset owner that is the subject of the estimate based on the calculated transition amount of 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 the threshold of the score based on the calculated score for the evaluation index and the asset owner required for the asset management plan; The calculated reference value is set as a threshold value for the score.

3. The information management system according to claim 2.

5. An information management method carried out by an information management system that supports the creation of an operation plan for package delivery using a computer having a processor and a memory, comprising: extracting assets available to a shipper from usage status data indicating usage status of assets of one or more asset owners used to deliver packages by EVs and delivery specifications of packages delivered by the shipper; reads out, for the asset owner of the extracted available assets from the assets owned by the asset owner and evaluation data for evaluating the asset owner, evaluation indicators regarding matters of interest that a shipper considers important when planning an operation of the asset; A score threshold for the evaluation index, which is 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 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; 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. Accumulating score history data for a plurality of asset owners, in which the calculated scores for the evaluation indexes are associated with the number of orders for the assets over a predetermined period; Among the accumulated score history data, among asset owners whose scores are close to a certain degree to the score for the evaluation index of the asset owner to be estimated, calculate the amount of transition of the score from the score transition history for the evaluation index of asset owners whose number of orders for the assets is improving; estimate the improved number of orders for the assets for the asset owner that is the subject of the estimate based on the calculated transition amount of 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 the threshold of the score based on the calculated score for the evaluation index and the asset owner required for the asset management plan; The calculated reference value is set as a threshold value for the score.

7. The information management method according to claim 6.

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