Group splicing method and device based on online car-hailing drivers

Abstract

The invention relates to the technical field of Internet travel, and discloses a group splicing method and device based on online car-hailing drivers. The method comprises the following steps: in response to a group building operation of a target driver, determining a target group splicing activity corresponding to a selection operation from a plurality of group splicing activities; in response to a sharing operation of the target driver for the target grouping activity, sharing invitation information of the target grouping activity to the first driver, and determining a grouping result of the target grouping activity in a preset time period; the first driver is other drivers except the target driver; when the grouping result meets a preset condition, determining that grouping succeeds; wherein the grouping success indicates that both the target driver and the first driver have the qualification of participating in the activity corresponding to the target grouping activity.

Description

Technical Field

[0001] The present invention relates to the field of Internet travel technology, and in particular to a group buying method and device based on online car-hailing drivers. Background Art

[0002] In related technologies, the platform displays high-value activity information to potential driver groups through channels such as search engine advertising, social media advertising, and travel-related application advertising.

[0003] However, high-value activity information displayed through engine ads, social media ads, and travel-related app ads cannot guarantee the driver group's trust in the high-value activity information, resulting in poor activity implementation results.

[0004] Therefore, how to improve the driver group's trust in high-value activity information becomes a technical problem that needs to be solved. Summary of the Invention

[0005] In view of this, the present invention provides a group-buying method and device based on online car-hailing drivers.

[0006] In a first aspect, the present invention provides a group buying method based on online car-hailing drivers, the method comprising: in response to a target driver's group creation operation, determining a target group buying activity corresponding to the selection operation from multiple group buying activities; in response to the target driver's sharing operation for the target group buying activity, sharing the invitation information of the target group buying activity to a first driver, and determining the group buying result of the target group buying activity within a preset time period; the first driver is a driver other than the target driver; when the group buying result meets the preset conditions, determining that the group buying is successful; wherein, the successful group buying indicates that the target driver and the first driver are both qualified to participate in the activity corresponding to the target group buying activity.

[0007] The group buying method based on online car-hailing drivers provided in this embodiment shares the invitation information with the first driver through the target driver, that is, a communication method based on direct social relationships between drivers, which takes advantage of the trust bond within the driver group. Drivers are more inclined to believe in recommendations from peers (especially drivers they are familiar with or respect) rather than official advertising information from the platform. Among them, when the target driver actively shares the group buying activity, his behavior itself is an endorsement of the activity. This endorsement will be transmitted through the social network between drivers, forming a word-of-mouth effect, thereby enhancing other drivers' trust in the activity.

[0008] Furthermore, group buying activities require a certain number of drivers (including the target driver and the first driver) to participate within a preset timeframe. This not only increases the fun and interactivity of the activity but also strengthens drivers' trust in the activity through collective participation. Drivers may believe that if other drivers are willing to participate, the activity must be credible and valuable.

[0009] In one possible implementation, the method also includes: obtaining relevant data of online car-hailing drivers; wherein the relevant data includes basic information data of the drivers, historical order data, and behavioral data; classifying the online car-hailing drivers based on the relevant data of the online car-hailing drivers, and determining the classification results corresponding to the online car-hailing drivers; utilizing a prediction model to determine the probability of the online car-hailing drivers participating in a target activity according to the classification results corresponding to the online car-hailing drivers; determining a plurality of activity rules according to the probability of the online car-hailing drivers participating in the target activity, and establishing a group buying activity corresponding to each of the plurality of activity rules according to the activity rules.

[0010] This embodiment provides a group-buying method for online ride-hailing drivers. By acquiring basic driver information, historical order data, and behavioral data, it provides a comprehensive and in-depth understanding of drivers' individual characteristics and operating habits. By categorizing drivers based on this rich data, drivers with similar characteristics can be accurately grouped together, providing a solid foundation for the precise planning of subsequent activities.

[0011] Furthermore, drivers of different categories differ in their operational goals and interests. Determining the probability of a driver's participation in a targeted activity based on this classification can more accurately assess drivers' interest and willingness to participate in different types of activities. Using this as a basis for determining activity rules can ensure that activity content is more tailored to drivers' actual needs, increasing their interest and enthusiasm for participation.

[0012] Furthermore, by analyzing driver data and predicting participation probabilities, the platform can more rationally allocate campaign resources, avoiding waste and ineffective investment. Driver groups with a higher probability of participation can be incentivized with more resources; while those with a lower probability of participation can be encouraged to participate by adjusting campaign rules or implementing other measures, thereby optimizing resource allocation.

[0013] In one possible implementation, determining the group buying result of a target group buying activity within a preset time period includes: responding to a second driver's participation operation for a target group buying activity of a target group in a public domain group, joining the target group, the public domain group includes multiple group buying activities, and the second driver is a driver who has not received invitation information for the target group buying activity; responding to a first driver's participation operation for the target group buying activity, joining the target group; determining the group buying result of the target group buying activity within the preset time period based on the number of first drivers and the number of second drivers.

[0014] The group buying method based on online car-hailing drivers provided in this embodiment breaks the limitation of traditional group buying activities relying solely on invitations to spread by allowing the second driver who has not received the invitation information for the target group buying activity to participate in the target group buying activity in the public domain group. The public domain group includes multiple group buying activities, which provides more drivers with opportunities to participate and can attract drivers from the platform's public domain traffic to join, greatly expanding the scope of participation in the activity. In addition, allowing the first driver to participate directly avoids the situation where the activity cannot be carried out due to insufficient number of participants. This flexible participation mechanism provides drivers with more opportunities to participate in activities and increases drivers' willingness to participate in activities.

[0015] In one possible implementation, the method also includes: when the validity period of the target group buying activity reaches the target validity period, removing the target driver and the first driver from the target group of the target group buying activity; and / or, in response to the first driver's withdrawal operation for the target group buying activity, removing the first driver from the target group corresponding to the target group buying activity.

[0016] The group buying method based on online car-hailing drivers provided in this embodiment removes the target driver and the first driver from the target group when the validity period of the target group buying activity reaches the target validity period, ensuring that the activity resources will not be occupied by some drivers for a long time. Activity resources such as reward quotas and preferential qualifications are limited. Timely cleaning up of participants in expired group buying activities can return these resources to the resource pool for use in subsequent new group buying activities, thereby improving resource utilization efficiency. In addition, in response to the first driver's withdrawal operation, he will be removed from the target group corresponding to the target group buying activity, fully respecting the driver's right of independent choice. Drivers may want to withdraw from the group buying activity for various reasons, such as scheduling conflicts, lack of interest in activity rewards, etc. This mechanism allows drivers to freely decide whether to continue to participate in the activity, thereby improving driver satisfaction.

[0017] In one possible implementation, in response to the target driver's sharing operation for the target group buying activity, the invitation information of the target group buying activity is shared with the first driver, including: in response to the target driver's sharing operation for the target group buying activity, determining the sharing method of the target group buying activity; wherein the sharing method includes at least one of text message, QR code and link; according to the sharing method, the invitation information of the target group buying activity is shared with the first driver.

[0018] This embodiment provides a group-sharing method for online ride-hailing drivers, offering multiple sharing methods such as text messages, QR codes, and links, to fully adapt to the target drivers' sharing needs in different scenarios. Each sharing method has its own advantages, and the target driver can choose the most appropriate method to share the invitation information with the first driver based on the actual situation.

[0019] In one possible implementation, the method further includes: when the target driver and the first driver both complete the target group buying activity, sending a first reward to the target driver based on the target driver's contribution, and sending a second reward to the first driver based on the first driver's contribution.

[0020] This embodiment provides a group-buying method for online ride-hailing drivers. Rewards are distributed based on the contribution of both the target driver and the first driver, accurately reflecting each driver's value in the group-buying activity. Contribution can be determined by taking into account multiple factors, such as the number of invitees, number of completed orders, and the effectiveness of the promotion. This personalized reward method allows drivers to feel recognized for their efforts and contributions, thereby motivating them to participate more actively in the activity.

[0021] In a second aspect, the present invention provides a group buying device based on online car-hailing drivers, which includes: a first determination module, used to respond to the target driver's group creation operation, and determine the target group buying activity corresponding to the selection operation from multiple group buying activities; a sharing determination module, used to respond to the target driver's sharing operation for the target group buying activity, share the invitation information of the target group buying activity to the first driver, and determine the group buying result of the target group buying activity within a preset time period; the first driver is a driver other than the target driver; a second determination module, used to determine that the group buying is successful when the group buying result meets the preset conditions; wherein, the successful group buying indicates that the target driver and the first driver are both qualified to participate in the activity corresponding to the target group buying activity.

[0022] In a third aspect, the present invention provides a computer device comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, computer instructions being stored in the memory, and the processor executing the computer instructions to execute the group-buying method based on online car-hailing drivers of the above-mentioned first aspect or any corresponding embodiment thereof.

[0023] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the group-buying method based on online car-hailing drivers of the above-mentioned first aspect or any corresponding embodiment thereof.

[0024] In a fifth aspect, the present invention provides a computer program product comprising computer instructions, the computer instructions being used to enable a computer to execute the group-buying method based on online car-hailing drivers of the above-mentioned first aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0026] Figure 1 1 is a flow chart of a group buying method based on online car-hailing drivers according to an embodiment of the present invention;

[0027] Figure 2 is a structural block diagram of a group-buying device based on online car-hailing drivers according to an embodiment of the present invention;

[0028] Figure 3 Schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0029] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative efforts shall fall within the scope of protection of the present invention.

[0030] According to an embodiment of the present invention, an embodiment of a group-buying method based on online car-hailing drivers is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0031] In this embodiment, a group-buying method based on online car-hailing drivers is provided, which can be used on computer devices such as computers, servers, etc. Figure 1 is a flow chart of a group-buying method based on online car-hailing drivers according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0032] Step S101 , in response to a target driver's group creation operation, determining a target group purchase activity corresponding to the selection operation from multiple group purchase activities.

[0033] The target driver can be the driver who initiates the group buying activity and is the initiator of the entire group buying process.

[0034] As an example, the target driver can be a driver who meets the qualifications for team formation. The qualifications for team formation may include a driver's service length exceeding a threshold (e.g., 5 years), a driver's positive review rate exceeding a threshold (e.g., 95%), a driver's order completion rate exceeding a threshold (e.g., 95%), etc., which are not specifically limited here.

[0035] The group creation operation can instruct the target driver to actively click "Create Group" or a similar button on the relevant interface of the online car-hailing platform to determine the behavior of a corresponding group purchase activity.

[0036] Multiple group buying activities may refer to a variety of group buying activity options with different types and reward mechanisms provided by the ride-hailing platform to drivers. Multiple group buying activities may be pre-determined group buying activities.

[0037] In a specific implementation, the group creation operation can be an operation generated by the target driver through a mouse click, keyboard selection, or touch screen. When the target driver issues a group creation operation on a webpage, the computer device can respond to the target driver's group creation operation on the webpage and determine the target group purchase activity corresponding to the selection operation from multiple group purchase activities.

[0038] For example, the platform sets up a dedicated group buying activity display page on the driver app or website. When the target driver enters this page, multiple group buying activities are displayed in the form of a list or cards. The target driver completes the group creation operation by clicking the "Select" or "Create Group" button of a group buying activity, and the activity is automatically selected as the target group buying activity.

[0039] For another example: If the driver side supports voice interaction function, the target driver can use voice commands, such as "I want to create a group, select [group buying activity name]". After recognizing the voice command, the specified group buying activity will be determined as the target group buying activity.

[0040] Step S102, in response to the target driver's sharing operation for the target group buying activity, sharing the invitation information of the target group buying activity to the first driver, and determining the group buying result of the target group buying activity within a preset time period; the first driver is a driver other than the target driver.

[0041] The first driver can indicate other drivers, besides the target driver, who have received the invitation and may participate in the target group buying activity. The invitation information may include relevant information about the target group buying activity, such as the activity name, activity rules, rewards, and how to participate, to attract other drivers to join the group buying activity. The preset time period can be a time range set by the platform, which is used to count participation in the target group buying activity during that time period to determine the group buying results.

[0042] In specific implementation, the sharing operation can be an operation generated by the target driver through a mouse click, keyboard selection, or touch screen. When the target driver issues a sharing operation on the mobile phone APP, the computer device can respond to the target driver's sharing operation and share the invitation information of the target group buying activity with the first driver.

[0043] As an example, the target driver selects the SMS sharing method on the sharing interface, enters the first driver's mobile phone number or selects a contact from the address book, and the platform sends the invitation information of the target group buying activity to the first driver in the form of a SMS.

[0044] As an example, the platform generates an exclusive QR code for the target group buying activity. The target driver can save the QR code to the mobile phone album and then share it with the first driver through social media, chat software, etc.; the QR code can also be directly displayed in the driver-side APP for the first driver to scan.

[0045] As an example, the platform generates an invitation link for the target group buying activity. The target driver can copy the link and share it on social media, driver communication groups, etc. The first driver clicks the link to view the invitation information and participate in the group buying.

[0046] After the target group buying activity is shared with the first driver, the group buying result of the target group buying activity within a preset time period can be determined.

[0047] As an example, the platform counts the number of drivers participating in the target group buying activity in real time within a preset time period and compares it with the preset threshold for successful group buying; or counts task indicators such as the number of orders completed by participating drivers to determine whether the preset conditions are met, thereby determining the group buying results.

[0048] For example, the target driver clicks the "Share" button on the target group buy event details page, selects the SMS sharing method, and enters the first driver's mobile phone number. The platform then sends a text message: "[Driver Name], the ride-hailing platform is launching a weekend group buy event. Complete 50 orders and receive an additional 200 yuan reward. Click [Link] to join the group buy and earn more together!" After receiving the text message, the first driver clicks the link to enter the event page. Simultaneously, the platform keeps real-time statistics on the number of drivers participating in the group buy event and the completion of orders. Assuming the preset time period is one week, the platform continuously updates the group buy progress during this week, and the group buy event page on the driver's app displays "3 drivers have participated, 2 more are needed to successfully join the group" and "20 orders have been completed, 30 more are needed to reach the target."

[0049] Step S103, when the group buying result meets the preset conditions, it is determined that the group buying is successful; wherein, the successful group buying indicates that both the target driver and the first driver are qualified to participate in the activity corresponding to the target group buying activity.

[0050] The preset conditions may indicate the criteria pre-set by the platform for determining whether a group purchase is successful, such as the number of drivers participating in the group purchase reaching a certain number, completing specific tasks, etc.

[0051] A successful group purchase indicates that the target group purchase activity meets the preset conditions. All drivers participating in the group purchase (target driver and first driver) are eligible to participate in subsequent activities corresponding to the target group purchase activity, such as obtaining rewards, enjoying specific order discounts, etc.

[0052] When the group buying result meets the preset conditions, the group buying is determined to be successful; wherein, the successful group buying indicates that both the target driver and the first driver are qualified to participate in the activity corresponding to the target group buying activity.

[0053] As an example, the platform can flexibly set pre-set conditions based on the campaign's goals and expected results. For example, a successful group buy could be considered only if the number of participating drivers reaches five, or a successful group buy could be considered only if the participating drivers complete a certain number of orders (e.g., 100) within a preset time period.

[0054] As an example, when the group purchase result meets the preset conditions, the platform sends a notification message to the target driver and the first driver, informing them that the group purchase is successful, and explains the rules for subsequent participation in activities and the method of reward distribution; at the same time, the status of the successful group purchase and information about available activities are displayed on the relevant page of the driver-side APP.

[0055] For example, the platform sets the preconditions of five drivers participating in a group share and completing 50 orders within a week. A week later, the platform finds that five drivers have participated and that the total number of orders has reached 50, thus satisfying the preconditions and confirming the group share success. The platform then sends a notification to the target driver and the first driver: "Congratulations on your successful participation in the weekend group share event! You are now eligible for subsequent events, and rewards will be credited to your account within three business days after the event ends." Drivers can then enjoy rewards and discounts in the subsequent events according to the rules.

[0056] The group buying method based on online car-hailing drivers provided in this embodiment shares the invitation information with the first driver through the target driver, that is, a communication method based on direct social relationships between drivers, which takes advantage of the trust bond within the driver group. Drivers are more inclined to believe in recommendations from peers (especially drivers they are familiar with or respect) rather than official advertising information from the platform. Among them, when the target driver actively shares the group buying activity, his behavior itself is an endorsement of the activity. This endorsement will be transmitted through the social network between drivers, forming a word-of-mouth effect, thereby enhancing other drivers' trust in the activity.

[0057] Furthermore, group buying activities require a certain number of drivers (including the target driver and the first driver) to participate within a preset timeframe. This not only increases the fun and interactivity of the activity but also strengthens drivers' trust in the activity through collective participation. Drivers may believe that if other drivers are willing to participate, the activity must be credible and valuable.

[0058] In one possible implementation, the method further includes:

[0059] Step S201, obtaining relevant data of the online car-hailing driver; wherein the relevant data includes the driver's basic information data, historical order data and behavior data.

[0060] Online ride-hailing drivers are drivers who register on online ride-hailing platforms and provide travel services. Driver basic information data may include basic information such as the driver's age, gender, driving experience, registration time, vehicle type, etc. Historical order data may indicate the order records completed by the driver on the online ride-hailing platform in the past period of time, such as the number of orders, order amount, order duration, passenger reviews, etc. Behavioral data may indicate the driver's operational behavior records on the platform, such as login frequency, order acceptance preferences (such as whether to give priority to long-distance orders, airport orders, etc.), number of order cancellations, history of participation in platform activities, etc.

[0061] As an example, an online ride-hailing platform stores various types of driver data in a database. By writing database query statements, it can directly extract the driver's basic information data, historical order data, and behavior data from the database.

[0062] As an example, if the platform's data is scattered across different systems, the required data can be obtained and integrated by calling the API interfaces provided by each system.

[0063] As an example, for some data that is difficult to obtain directly, such as the driver's special skills certificate information, a form can be designed to allow the driver to actively upload relevant data.

[0064] Step S202: Classify the online car-hailing drivers based on their relevant data and determine the classification results corresponding to the online car-hailing drivers.

[0065] The classification results can indicate the specific category to which each driver belongs, such as high-activity driver, low-activity driver, high-quality service driver, novice driver, etc.

[0066] As an example, algorithms such as K-means clustering and hierarchical clustering can be used to automatically classify drivers into different categories based on their relevant data characteristics. For example, clustering can be performed based on indicators such as the number of historical orders, order amount, and login frequency.

[0067] As an example, a decision tree model is constructed to gradually divide drivers into different categories based on different driver characteristics (such as driving experience, registration time, and passenger reviews). For example, drivers are first divided into two categories based on whether they have more than three years of driving experience, and each category is further divided based on whether they registered within one year.

[0068] As an example, a series of classification rules are developed based on business experience and industry knowledge to classify drivers.

[0069] For example, drivers with over 1,000 orders and an average passenger rating of 4.8 or higher are considered high-quality drivers. The online ride-hailing platform retrieved data related to driver Zhang San from its database: Driver Basic Information: Age 35, Male, 8 years of driving experience, Registration Date January 2020, Vehicle Type Comfort Sedan. Historical Order Data: 1,200 orders completed in the past year, total order value 150,000 yuan, average order duration 30 minutes, average passenger rating 4.9. Behavioral Data: Logged in to the platform six days a week, preferred long-distance orders, canceled orders five times in the past year, and participated in two platform-sponsored order-taking incentive programs. Based on this data, cluster analysis was used to categorize drivers. Using driver age, registration time, number of orders, and passenger ratings as features, the K-means clustering algorithm was used to categorize drivers into three categories: High-Activity High-Quality Drivers: Long driving experience, early registration, high number of orders, and high passenger ratings. Driver Zhang San was classified into this category. Moderately active drivers: All indicators are at a medium level. Low-activity novice drivers: Short driving experience, late registration, and few orders.

[0070] Step S203: Using the prediction model, the probability of the online car-hailing driver participating in the target activity is determined according to the classification results corresponding to the online car-hailing driver.

[0071] A prediction model refers to a model built using statistical or machine learning algorithms, used to predict a target variable (here, the probability of participating in a target activity) based on input features (here, the driver's classification results). A target activity is a specific campaign planned by the ride-hailing platform, such as a holiday order-taking incentive program or a new user referral program. The probability of participating in a target activity indicates the likelihood that a driver will participate in the target activity.

[0072] The prediction model is used to determine the probability of the online ride-hailing driver participating in the target activity based on the classification results corresponding to the online ride-hailing driver. The classification results corresponding to the online ride-hailing driver can be used as the input of the prediction model, and the probability of the online ride-hailing driver participating in the target activity can be used as the output of the prediction model.

[0073] As an example, a logistic regression model is constructed using the driver classification results as features and the driver's participation in the target activity (participation or non-participation) as the target variable. The model parameters are learned from the training data, and the trained model is then used to predict the probability of a new driver participating in the target activity.

[0074] As an example, the random forest algorithm is used to build multiple decision tree models based on multiple features such as the driver's classification results. Then, the probability prediction results of the driver's participation in the target activity are obtained by voting or averaging.

[0075] As an example, for complex data relationships, a neural network model, such as a multi-layer perceptron (MLP), can be used to predict the driver's participation probability through nonlinear transformation of multiple layers of neurons.

[0076] Step S204: Determine multiple activity rules based on the probability of online car-hailing drivers participating in the target activity, and establish a group buying activity corresponding to each of the multiple activity rules.

[0077] Activity rules can indicate the specific rules and conditions established for conducting group buying activities, such as the number of group members required, the activity time range, and the reward settings. Group buying activities can also indicate a form of marketing activity where drivers can invite other drivers to form a group and share the activity rewards after meeting certain conditions.

[0078] As an example, consider a probability interval classification rule: based on the probability of a driver participating in the target activity, drivers are divided into different probability intervals, such as 0-0.3, 0.3-0.6, and 0.6-1. Different activity rules are developed for each probability interval. For example, for drivers with a participation probability of 0.6-1, the group membership requirement is 3; for drivers with a participation probability of 0.3-0.6, the group membership requirement is 5. Then, corresponding group activities are established based on each rule.

[0079] As an example, the platform can dynamically adjust activity rules based on its activity goals and resource availability. For example, if the platform wants to attract more drivers with a lower probability of participation, it can appropriately lower the group size requirement for these drivers or increase the reward amount.

[0080] As an example, you can design multiple sets of different campaign rules, establish corresponding group buying campaigns for each, and conduct A / B testing. By comparing indicators such as the number of participants and effectiveness of group buying campaigns under different rules, you can select the optimal campaign rules for large-scale promotion.

[0081] For example: Based on the probability of drivers participating in the target activity, drivers are divided into three probability intervals: 0-0.5, 0.5-0.8, and 0.8-1. Develop activity rules for each interval and establish group buying activities: For drivers with a participation probability of 0-0.5: the number of group members must be 8, the activity time is one week before National Day, and the reward is an additional reward of 5 yuan for each completed order. For drivers with a participation probability of 0.5-0.8: the number of group members must be 5, the activity time is during National Day, and the reward is an additional reward of 8 yuan for each completed order. For drivers with a participation probability of 0.8-1 (such as Zhang San): the number of group members must be 3, the activity time is during National Day, the reward is an additional reward of 10 yuan for each completed order, and a gas card worth 50 yuan can be obtained after the group is successfully formed. Then, according to these rules, corresponding group buying activity pages are established and launched on the driver-side APP.

[0082] This embodiment provides a group-buying method for online ride-hailing drivers. By acquiring basic driver information, historical order data, and behavioral data, it provides a comprehensive and in-depth understanding of drivers' individual characteristics and operating habits. By categorizing drivers based on this rich data, drivers with similar characteristics can be accurately grouped together, providing a solid foundation for the precise planning of subsequent activities.

[0083] Furthermore, drivers of different categories differ in their operational goals and interests. Determining the probability of a driver's participation in a targeted activity based on this classification can more accurately assess drivers' interest and willingness to participate in different types of activities. Using this as a basis for determining activity rules can ensure that activity content is more tailored to drivers' actual needs, increasing their interest and enthusiasm for participation.

[0084] Furthermore, by analyzing driver data and predicting participation probabilities, the platform can more rationally allocate campaign resources, avoiding waste and ineffective investment. Driver groups with a higher probability of participation can be incentivized with more resources; while those with a lower probability of participation can be encouraged to participate by adjusting campaign rules or implementing other measures, thereby optimizing resource allocation.

[0085] In one possible implementation, determining the group buying result of the target group buying activity within the preset time period in step S102 includes:

[0086] Step S1021, in response to the second driver's participation operation for the target group buying activity of the target group in the public domain group, join the target group, the public domain group includes multiple group buying activities, and the second driver is a driver who has not received the invitation information of the target group buying activity.

[0087] The second driver can be a driver who has not received an invitation to the target group buying activity, but has proactively discovered and participated in the target group buying activity in the public domain group. The public domain group can indicate an open group buying activity collection area on the online ride-hailing platform, where all drivers can view and participate in the group buying activities. The target group can indicate a driver group formed for the target group buying activity. When a driver participates in the target group buying activity, he or she will be added to this target group. The target group buying activity can indicate a specific group buying activity with corresponding rules and reward mechanisms, and drivers can choose to participate.

[0088] As an example, on the public group page of the driver-side APP, when the second driver clicks the "Participate" button of the target group activity, the system detects the click event through the front-end code and sends the relevant information to the back-end server for processing to complete the operation of joining the target group.

[0089] As an example, if the driver side supports voice interaction, the second driver says voice commands such as "I want to participate in [target group buying activity name]", and the voice recognition system converts the voice into text. The system then adds the second driver to the target group according to the command.

[0090] In one possible implementation, after detecting the second driver's participation, the platform directly adds the second driver's information to the target group's data list and updates the target group's participant statistics. For some specific targeted group buying activities, platform review may be required before participation. For example, if the activity has requirements for the driver's service rating, the system will first check whether the second driver's service rating meets the requirements. If it does, the driver will be added to the target group. If not, the driver will be prompted that they do not meet the requirements.

[0091] Step S1022: In response to the first driver's participation operation for the target group buying activity, join the target group.

[0092] The participation operation can be an operation generated by the target driver through a mouse click, keyboard selection, or touch screen. When the target driver performs the participation operation for the target group buying activity, the computer device can respond to the participation operation of the first driver and join the target group.

[0093] As an example, after receiving the invitation information of the target group buying activity, the first driver clicks the link in the information and directly jumps to the participation page of the target group buying activity, and clicks the "Participate" button on the page to complete the operation.

[0094] As an example, the invitation message contains a QR code for the target group buying activity. The first driver uses the driver-side APP to scan the QR code, enter the activity page and participate.

[0095] Step S1023: Determine the group buying result of the target group buying activity within a preset time period according to the number of the first drivers and the number of the second drivers.

[0096] The platform pre-sets a threshold for successful group placement. After the preset time period, the system counts the total number of first and second drivers and compares it with the threshold. If the total number is greater than or equal to the threshold, the group placement is successful; otherwise, it fails.

[0097] In one possible implementation, in addition to the number of people required, other rules may also be combined, such as the average service rating of participating drivers, the number of completed orders, etc. The system determines the group purchase result based on these comprehensive rules.

[0098] In one scenario, the ride-hailing platform provided a public group entry on the driver app's homepage. This public group offered multiple promotions, such as "Group buy during weekends, complete 30 orders and receive an additional 150 yuan reward," and "Group buy during peak hours, achieve a 120 yuan reward for reaching a target acceptance rate." Driver Li Si, upon entering the public group page, saw the target group promotion, "Group buy during weekends, complete 30 orders and receive an additional 150 yuan reward." He thought the reward was attractive and clicked the "Join" button. The system detected Li Si's participation, added him to the target group for the promotion, and updated the target group's participant count to one.

[0099] After launching the "Weekend group ordering event, complete 30 orders and receive an additional 150 yuan reward," the target driver, Wang Wu, sent an invitation via text message to the first driver, Zhao Liu. Zhao Liu clicked the link in the message and was redirected to the target group ordering page. After viewing the event rules and rewards, he clicked "Participate." The system responded to Zhao Liu's action and added him to the target group order, bringing the number of participants to two.

[0100] The platform sets a threshold of 5 people for a successful group purchase, and the preset time period is one week. During this week, the system continuously counts the number of first and second drivers who join the target group. By the end of the week, the statistics show that a total of 6 drivers have joined the target group (3 of whom are first drivers and 3 are second drivers). Since 6 is greater than 5, the system determines that the target group purchase activity is successful, and sends a notification to the target driver Wang Wu and all participating drivers: "Congratulations on your successful participation in the weekend order group purchase activity! You can claim an additional reward of 150 yuan according to the rules after the activity ends." At the same time, the target group purchase activity page on the driver-side APP also displays the status of the successful group purchase.

[0101] The group buying method based on online car-hailing drivers provided in this embodiment breaks the limitation of traditional group buying activities relying solely on invitations to spread by allowing the second driver who has not received the invitation information for the target group buying activity to participate in the target group buying activity in the public domain group. The public domain group includes multiple group buying activities, which provides more drivers with opportunities to participate and can attract drivers from the platform's public domain traffic to join, greatly expanding the scope of participation in the activity. In addition, allowing the first driver to participate directly avoids the situation where the activity cannot be carried out due to insufficient number of participants. This flexible participation mechanism provides drivers with more opportunities to participate in activities and increases drivers' willingness to participate in activities.

[0102] In one possible implementation, the method further includes:

[0103] Step S301: When the validity period of the target group buying activity reaches the target validity period, the target driver and the first driver are removed from the target group of the target group buying activity.

[0104] Target validity period: A pre-set time limit for the target group buying activity. When this time point is reached, the activity ends.

[0105] When the target group buy activity reaches its pre-determined validity period, the system will automatically remove the target driver who initiated the activity and the first driver who received the invitation and participated from the target group. This action marks the end of the target group buy activity in terms of time, and the relevant drivers are no longer participating in the activity.

[0106] As an example, when the system creates a target group purchase activity, it records the activity's start time and target validity period, calculates the activity's end time (start time + target validity period), and stores it as a timestamp. During system operation, the system periodically obtains the current time's timestamp (e.g., every minute) and compares it with the activity's end time's timestamp. If the current time is greater than or equal to the end time, the target group purchase activity's validity period is determined to have reached the target validity period.

[0107] As an example, use a scheduled task scheduling tool (such as Linux's crontab, Java's TimerTask, etc.) to set a scheduled task at the start of the target group purchase activity, which is triggered at the end of the target validity period. When the scheduled task is triggered, the target driver and the first driver are removed from the target group.

[0108] As an example, in the database, the target group of a target group buying activity is usually stored as a collection of driver IDs. When the validity period reaches the target validity period, the system directly deletes the target driver and the first driver's ID from the data record of the target group.

[0109] For example, instead of directly deleting the data, a status flag field, such as "Expired," is added to the driver's participation record. When the validity period reaches the target validity period, the field is marked as "Expired" for both the target driver and the first driver. Subsequent business logic uses this flag to determine whether the driver is still participating in the activity.

[0110] This embodiment provides a group-buying method for online ride-hailing drivers. When the target group-buying activity reaches its target validity period, the target driver and the first driver are removed from the target group, ensuring that activity resources are not occupied by a few drivers for a long time. Activity resources, such as reward quotas and preferential qualifications, are limited. Promptly clearing participants from expired group-buying activities allows these resources to be returned to the resource pool for use in subsequent new group-buying activities, thereby improving resource utilization efficiency.

[0111] In one possible implementation, the method further includes:

[0112] Step S302: In response to the first driver's withdrawal operation from the target group buying activity, the first driver is removed from the target group corresponding to the target group buying activity.

[0113] When the first driver who receives the invitation to the target group buying activity initiates the withdrawal operation, the system will respond to this operation and remove the first driver from the target group corresponding to the target group buying activity. This means that the driver has voluntarily given up the qualification to participate in the target group buying activity.

[0114] As an example, a "Leave Group" button is set on the target group purchase activity details page of the driver app. When the first driver clicks the button, the front-end code detects the click event and sends a leave request to the back-end server.

[0115] As an example, if the driver side supports voice interaction, the first driver says a voice command such as "I want to quit [target group buying activity name]", and after the voice recognition system converts the voice into text, the system triggers the withdrawal operation according to the command.

[0116] As an example, after receiving the withdrawal request from the first driver, the backend server immediately deletes the ID of the first driver from the data record of the target group and updates the statistics of the number of participants in the target group.

[0117] For example, considering system performance and stability, the withdrawal request might be placed in a message queue and processed asynchronously by a dedicated consumer process. After receiving the withdrawal request from the message queue, the consumer process removes the first driver from the target group.

[0118] This embodiment provides a group-buying method for online ride-hailing drivers. Upon a driver's withdrawal from a group, the driver is removed from the target group for the targeted group-buying activity, fully respecting the driver's right to choose independently. Drivers may wish to withdraw from a group-buying activity for various reasons, such as scheduling conflicts or lack of interest in the activity rewards. This mechanism allows drivers to freely decide whether to continue participating in the activity, improving driver satisfaction.

[0119] In one possible implementation, the method further includes:

[0120] Step S301: When the validity period of the target group buying activity reaches the target validity period, the target driver and the first driver are removed from the target group of the target group buying activity.

[0121] Step S302: In response to the first driver's withdrawal operation from the target group buying activity, the first driver is removed from the target group corresponding to the target group buying activity.

[0122] In one scenario, Zhang San, an online car-hailing driver, launched a target group buying activity called "Accept orders and group buy during the May Day holiday, and get an extra reward of 200 yuan for completing 50 orders". The target validity period was set to 5 days, starting from April 28. When the system created the activity, it recorded the start time and validity period, and calculated the end time to be May 2. During the operation of the system, the scheduled task checks the current time every hour. When 0:00 on May 2, the scheduled task is triggered, and the system determines that the validity period of the target group buying activity has reached the target validity period. Subsequently, the system deleted Zhang San (the target driver) and the driver IDs of Li Si and Wang Wu (the first driver) who received the invitation information and participated in the activity from the data records of the target group in the database, and removed them from the target group. At the same time, the target group buying activity page of the driver-side APP shows that the activity has ended and the relevant drivers are no longer participating.

[0123] In one scenario, ride-hailing driver Zhao Liu received an invitation to a targeted group buy event initiated by driver Sun Qi, titled "Accept group buy orders during peak weekend hours, and receive a 100 yuan reward for meeting the acceptance rate target." He then joined the target group. However, during the event, Zhao Liu decided not to continue participating for personal reasons. So, Zhao Liu opened the driver app, accessed the target group buy event details page, and clicked the "Quit" button. The front-end code detected the click event and sent the quit request to the back-end server. Upon receiving the request, the back-end server immediately deleted Zhao Liu's driver ID from the target group's data record and updated the number of participants in the target group. At the same time, a notification was sent to Zhao Liu: "You have successfully exited the weekend peak hour group buy event." On the target group buy event page of the driver app, Zhao Liu's status was also displayed as "Quitted."

[0124] The group buying method based on online car-hailing drivers provided in this embodiment removes the target driver and the first driver from the target group when the validity period of the target group buying activity reaches the target validity period, ensuring that the activity resources will not be occupied by some drivers for a long time. Activity resources such as reward quotas and preferential qualifications are limited. Timely cleaning up of participants in expired group buying activities can return these resources to the resource pool for use in subsequent new group buying activities, thereby improving resource utilization efficiency. In addition, in response to the first driver's withdrawal operation, he will be removed from the target group corresponding to the target group buying activity, fully respecting the driver's right of independent choice. Drivers may want to withdraw from the group buying activity for various reasons, such as scheduling conflicts, lack of interest in activity rewards, etc. This mechanism allows drivers to freely decide whether to continue to participate in the activity, thereby improving driver satisfaction.

[0125] In one possible implementation, in response to the target driver's sharing operation for the target group buying activity, sharing the invitation information of the target group buying activity to the first driver in step S102 includes:

[0126] Step S102A, in response to the target driver's sharing operation for the target group buying activity, determining a sharing method for the target group buying activity; wherein the sharing method includes at least one of a text message, a QR code, and a link.

[0127] When the target driver performs a sharing operation for the target group buying activity, the system will respond to the operation and determine the sharing method used for the target group buying activity. There are multiple sharing methods to choose from, including but not limited to SMS, QR code, and link. The target driver can select at least one of these options to share.

[0128] As an example, set a share button (such as a "Share" icon or text button) on the target group buying activity page of the driver-side app. When the target driver clicks the button, the front-end code detects the click event, triggers the sharing operation response process, and pops up a sharing method selection interface for the target driver to select a sharing method.

[0129] For example, if the driver's app supports gestures, such as setting a specific gesture (such as swiping up from the bottom of the screen) to trigger the sharing action, when the target driver makes the gesture, the system detects the action through the gesture recognition algorithm and enters the sharing method selection process.

[0130] Step S102B: Share the invitation information of the target group buying activity to the first driver according to the sharing method.

[0131] After determining the sharing method of the target group buying activity, the system will send the invitation information of the target group buying activity to the first driver according to the selected sharing method, so that the first driver can receive relevant information about the activity and have the opportunity to participate.

[0132] This embodiment provides a group-sharing method for online ride-hailing drivers, offering multiple sharing methods such as text messages, QR codes, and links, to fully adapt to the target drivers' sharing needs in different scenarios. Each sharing method has its own advantages, and the target driver can choose the most appropriate method to share the invitation information with the first driver based on the actual situation.

[0133] In one possible implementation, the above method also includes: when the target driver and the first driver both complete the target group buying activity, sending a first reward to the target driver based on the target driver's contribution, and sending a second reward to the first driver based on the first driver's contribution.

[0134] When both the target driver and the first driver successfully complete the tasks or conditions set by the target group buying activity, the system will enter the reward distribution process. This process will send the first reward and the second reward to the target driver and the first driver respectively based on their contribution to the activity.

[0135] Contribution can indicate the degree of contribution a driver has made to the target group-buying activity, typically measured by the number, quality, and efficiency of completed tasks. The first reward can indicate the reward the system sends to the target driver based on their contribution. The second reward can indicate the reward the system sends to the first driver based on their contribution.

[0136] As an example, the system can calculate a driver's contribution based on the number of tasks they complete in a targeted group buying activity. For example, a targeted group buying activity requires a driver to complete a certain number of orders within a specific time period. The more orders a driver completes, the higher the contribution.

[0137] As an example, in addition to the number of tasks, the system can also consider the quality of the tasks. For example, in online ride-hailing group activities, the driver's service score and passenger praise rate can be used as indicators to measure contribution.

[0138] As an example, the system can also calculate the driver's contribution based on the speed or efficiency with which the driver completes tasks. For example, a driver who completes more orders in a shorter time can receive a higher contribution.

[0139] As an example, after a driver completes a target group purchase activity, the system can immediately calculate the reward based on the contribution and directly pay the reward into the driver's account.

[0140] As an example, to ensure the fairness and accuracy of the event, the system may distribute rewards within a period of time after the event (such as a day or a week) to enable a more comprehensive review and calculation of the driver's contribution.

[0141] As an example, the system can set different levels of rewards based on contribution. For example, drivers with high contribution can receive higher-level rewards, such as cash bonuses, coupons, etc., while drivers with low contribution may receive lower-level rewards or only receive participation rewards.

[0142] In one scenario, ride-hailing driver Zhang San launched a targeted group buy event: "Complete 50 orders during the May Day holiday and receive an additional 200 yuan reward." He invited top drivers Li Si and Wang Wu to participate. During the May Day holiday, Zhang San, Li Si, and Wang Wu actively participated in accepting orders and diligently completed the event's objectives. After the holiday, the system compiled statistics on each driver's order intake and service ratings. Zhang San, the target driver, completed 55 orders with a service rating of 4.9; Li Si completed 48 orders with a service rating of 4.8; and Wang Wu completed 52 orders with a service rating of 4.7. Based on the event rules, the system calculated each driver's contribution. Zhang San had the highest contribution, as he not only completed the most orders but also had the highest service rating. Wang Wu ranked second, while Li Si, despite completing more orders, had a slightly lower service rating, resulting in a relatively low contribution. Ultimately, based on their contribution, the system awarded Zhang San the primary reward—a 300 yuan cash red envelope; and Li Si and Wang Wu received secondary rewards: coupons worth 200 and 250 yuan, respectively. Drivers received reward notifications in the driver app and can use these rewards in subsequent orders.

[0143] This embodiment provides a group-buying method for online ride-hailing drivers. Rewards are distributed based on the contribution of both the target driver and the first driver, accurately reflecting each driver's value in the group-buying activity. Contribution can be determined by taking into account multiple factors, such as the number of invitees, number of completed orders, and the effectiveness of the promotion. This personalized reward method allows drivers to feel recognized for their efforts and contributions, thereby motivating them to participate more actively in the activity.

[0144] In this embodiment, a group-buying device based on online car-hailing drivers is also provided, which is used to implement the above-mentioned embodiments and preferred embodiments, and those that have been described will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceived.

[0145] This embodiment provides a group-buying device based on online car-hailing drivers, such as Figure 2As shown, the device includes: a first determination module 201, which is used to respond to the target driver's group creation operation and determine the target group activity corresponding to the selection operation from multiple group activities; a sharing determination module 202, which is used to respond to the target driver's sharing operation for the target group activity, share the invitation information of the target group activity to the first driver, and determine the group result of the target group activity within a preset time period; the first driver is a driver other than the target driver; a second determination module 203, which is used to determine that the group is successful when the group result meets the preset conditions; wherein, the successful group indicates that the target driver and the first driver are both qualified to participate in the activity corresponding to the target group activity.

[0146] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0147] The group-buying device based on online car-hailing drivers in this embodiment is presented in the form of a functional unit, where the functional unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0148] The embodiment of the present invention also provides a computer device having the above Figure 2 The group-buying device based on online car-hailing drivers is shown.

[0149] See also Figure 3 , Figure 3 is a structural diagram of a computer device provided by an optional embodiment of the present invention, such as Figure 3 As shown, the computer device includes: one or more processors 10, memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components utilize different buses to communicate with each other and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in the memory or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Equally, multiple computer devices can be connected, and each device provides part of the necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 3 A processor 10 is taken as an example.

[0150] The processor 10 may be a central processing unit, a network processor, or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic, or any combination thereof.

[0151] The memory 20 stores instructions that can be executed by at least one processor 10, so as to enable at least one processor 10 to execute the method shown in the above embodiment.

[0152] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and application programs required for at least one function; the data storage area may store data created based on the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0153] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0154] The computer device further includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30 and the output device 40 may be connected via a bus or other means. Figure 3 The bus connection is taken as an example.

[0155] The input device 30 can receive input digital or character information and generate key signal input related to user settings and function control of the computer device, such as a touch screen, a keypad, a mouse, a trackpad, a touch pad, an indicator stick, one or more mouse buttons, a trackball, a joystick, etc. The output device 40 can include a display device, an auxiliary lighting device (e.g., an LED), and a tactile feedback device (e.g., a vibration motor). The above-mentioned display device includes but is not limited to a liquid crystal display, a light emitting diode, a display, and a plasma display. In some optional embodiments, the display device can be a touch screen.

[0156] The computer device further includes a communication interface for the computer device to communicate with other devices or a communication network.

[0157] The embodiment of the present invention also provides a computer-readable storage medium. The above-mentioned method according to the embodiment of the present invention can be implemented in hardware, firmware, or implemented as a computer code that can be recorded in a storage medium, or implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and downloaded through a network and will be stored in a local storage medium, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state drive, etc.; further, the storage medium can also include a combination of the above-mentioned types of memory. It can be understood that a computer, a processor, a microprocessor controller or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor or hardware, the method shown in the above embodiment is implemented.

[0158] A portion of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the form in which the computer program instruction exists in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc. Accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium that can be accessed by the computer.

[0159] Although the embodiments of the present invention have been described with reference to the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention. Such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A group buying method based on online car-hailing drivers, characterized in that: The method comprises: In response to a group creation operation by a target driver, determining a target group purchase activity corresponding to the selection operation from multiple group purchase activities; In response to a target driver's sharing operation for a target group buying activity, sharing the target group buying activity invitation information with a first driver, and determining a group buying result of the target group buying activity within a preset time period; the first driver is a driver other than the target driver; When the group buying result meets the preset conditions, the group buying is determined to be successful; wherein, the successful group buying indicates that both the target driver and the first driver are qualified to participate in the activity corresponding to the target group buying activity.

2. The group buying method based on online car-hailing drivers according to claim 1 is characterized in that: The method further comprises: Obtaining relevant data of online ride-hailing drivers; wherein the relevant data includes basic information data of drivers, historical order data and behavior data; Classify the online ride-hailing drivers based on the relevant data of the online ride-hailing drivers and determine the classification results corresponding to the online ride-hailing drivers; Using the prediction model, based on the classification results corresponding to the online ride-hailing driver, determine the probability of the online ride-hailing driver participating in the target activity; Based on the probability of the online car-hailing driver participating in the target activity, multiple activity rules are determined, and based on each of the multiple activity rules, a group buying activity corresponding to the activity rule is established.

3. The group buying method based on online car-hailing drivers according to claim 1 is characterized in that: Determining the group buying result of the target group buying activity within a preset time period includes: In response to a second driver's participation operation for a target group buying activity of a target group in a public domain group, joining the target group, the public domain group including multiple group buying activities, the second driver being a driver who has not received invitation information for the target group buying activity; In response to a first driver's participation operation for a target group buying activity, joining the target group; The group buying result of the target group buying activity within a preset time period is determined according to the number of the first drivers and the number of the second drivers.

4. The group buying method based on online car-hailing drivers according to claim 1 is characterized in that: The method further comprises: When the validity period of the target group buying activity reaches a target validity period, removing the target driver and the first driver from the target group of the target group buying activity; and / or, In response to the first driver's withdrawal operation for the target group buying activity, the first driver is removed from the target group corresponding to the target group buying activity.

5. The group buying method based on online car-hailing drivers according to claim 1 is characterized in that: In response to a target driver's sharing operation for a target group buying activity, sharing the target group buying activity invitation information to the first driver includes: In response to a target driver's sharing operation for a target group buying activity, determining a sharing method for the target group buying activity; wherein the sharing method includes at least one of a text message, a QR code, and a link; According to the sharing method, the invitation information of the target group buying activity is shared with the first driver.

6. The group buying method based on online car-hailing drivers according to claim 1 is characterized in that: The method further comprises: When both the target driver and the first driver complete the target group buying activity, a first reward is sent to the target driver according to the contribution of the target driver, and a second reward is sent to the first driver according to the contribution of the first driver.

7. A group-buying device based on online car-hailing drivers, characterized in that: The device comprises: A first determining module is configured to determine a target group buying activity corresponding to the selection operation from multiple group buying activities in response to a group creating operation by a target driver; a sharing determination module, configured to, in response to a target driver's sharing operation for a target group buying activity, share the invitation information of the target group buying activity with a first driver, and determine a group buying result of the target group buying activity within a preset time period; the first driver is a driver other than the target driver; The second determination module is used to determine that the group purchase is successful when the group purchase result meets the preset conditions; wherein, the successful group purchase indicates that the target driver and the first driver are both qualified to participate in the activity corresponding to the target group purchase activity.

8. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, computer instructions are stored in the memory, and the processor executes the group-buying method based on online car-hailing drivers as described in any one of claims 1 to 6 by executing the computer instructions.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, which are used to enable a computer to execute the group-buying method based on online car-hailing drivers as described in any one of claims 1 to 6.

10. A computer program product, characterized in that It includes computer instructions, which are used to enable a computer to execute the group buying method based on online car-hailing drivers as described in any one of claims 1 to 6.

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