SYSTEM AND METHOD FOR INTERMEDIARY AGENCY TO FIND BETTER SERVICE PROVIDERS

• US 20160180346A1
• Filed: 12/19/2014
• Published: 06/23/2016
• Est. Priority Date: 12/19/2014
• Status: Active Grant

• Current Assignee: SAP SE
• Original Assignee: Cheng, Yu, Mengjiao Wang, Wen-Syan Li
• Inventors: CHENG, Yu, WANG, Mengjiao, LI, Wen-Syan
• Granted Patent: US 10,083,448 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06Q 30/016 After-sales
• CPC Class Codes: G06Q 50/40 Business processes related to the transportation industry shipping G06Q10/083

Abstract

Disclosed herein is a framework for determining a service provider to service a customer request. In accordance with one aspect, a request from a customer is received by a decision module. The decision module further receives a response to the request from a first service provider, determines the average frequency of responses for a given time interval during the time and location of the request, estimates arrival time of the first service provider and near-by service providers to the location of the customer, ranks all service providers based on arrival time, and estimates a probability of a shorter customer wait time.

Claims

1. A computer implemented method for determining a service provider to service a customer request comprising:

receiving a request from a customer by a decision module, the request includes time of request and location of the customer;

receiving a response to the request from a first service provider by the decision module, wherein the response indicates that the first service provider desires to service the request;

determining, by the decision module, the average frequency of responses for a given time interval during the time and location of the request;

estimating, by the decision module, arrival time of the first service provider and near-by service providers to the location of the customer;

ranking all service providers based on arrival time;

estimating a probability of a shorter customer wait time;

if the probability of a shorter customer wait time is high,

(i) wait for a service provider with shorter customer wait time to respond to the request,

(ii) issue an order to the service provider with the shorter customer wait time to service the request, and

(iii) if no service provider with shorter customer wait time responds to the request within a prescribed period of time, issue the order to the first service provider to service the request; and

if the probability of a shorter customer wait time is low, issue the order to the first service provider to service the request.

2. The method of claim 1, wherein the service provider is a taxi driver and the customer is a passenger.

3. The method of claim 1, wherein the request is received from a mobile device of the customer.

4. The method of claim 1, wherein the average frequency of responses for a given time interval is based on historical records of taxi responses.

5. The method of claim 1, wherein the average frequency of responses is a Poisson distribution.

6. The method of claim 1, wherein the arrival time is estimated based on real-time data.

7. The method of claim 6, wherein the real-time data comprises data from a geographical information system (GIS) service.

8. The method of claim 1 wherein estimating a probability of shorter customer wait time comprises using

9. A decision module for determining a service provider to service a customer request comprising:

a storage for storing historical records of service provider responses, service provider distribution data, GIS data and real time traffic data; and

a processor, wherein the processor is coupled to the storage, the processor is configured to receive a request from a customer for service from a service provider and a response to the request by a first service provider to service the request, the processor comprises,

a time arrival estimator, the time arrival estimator estimates arrival time of the first service provider to the customer and arrival times of near-by service providers from the service provider distribution data,

a decision-making handler, wherein the decision making handler comprises,

a service provider response probability model for determining a number of service providers which may respond to the request, and

a customer waiting time reduction probability model for determining a probability of a shorter wait time for the customer to have the request serviced, wherein the decision-making handler decides,

if the probability of a shorter customer wait time is high,

(i) wait for a service provider with shorter customer wait time to respond to the request,

(ii) issue an order to the service provider with the shorter customer wait time to service the request, and

(iii) if no service provider with shorter customer wait time responds to the request within a prescribed period of time, issue the order to the first service provider to service the request; and

if the probability of a shorter customer wait time is low, issue the order to the first service provider to service the request.

10. The device of claim 9, wherein the service providers are taxis and the customers are passengers.

11. The method of claim 9, wherein the arrival time is estimated based on real-time data.

12. The method of claim 11, wherein the real-time data comprises data from a geographical information system (GIS) service.

13. The method of claim 9 wherein the customer waiting time reduction probability model comprises

14. The device of claim 9, wherein the service provider response probability model comprises

15. A non-transitory computer-readable medium having stored thereon program code, the program code executable by a computer for determining a service provider to service a customer request comprising:

receiving a request from a customer by a decision module, the request includes time of request and location of the customer;

receiving a response to the request from a first service provider by the decision module, wherein the response indicates that the first service provider desires to service the request;

determining, by the decision module, the average frequency of responses for a given time interval during the time and location of the request;

estimating, by the decision module, arrival time of the first service provider and near-by service providers to the location of the customer;

ranking all service providers based on arrival time;

estimating a probability of a shorter customer wait time;

if the probability of a shorter customer wait time is high,

(i) wait for a service provider with shorter customer wait time to respond to the request,

(ii) issue an order to the service provider with the shorter customer wait time to service the request, and

(iii) if no service provider with shorter customer wait time responds to the request within a prescribed period of time, issue the order to the first service provider to service the request; and

if the probability of a shorter customer wait time is low, issue the order to the first service provider to service the request.

16. The non-transitory computer-readable medium of claim 15, wherein the average frequency of responses for a given time interval is based on historical records of taxi responses.

17. The non-transitory computer-readable medium of claim 15, wherein the average frequency of responses is a Poisson distribution.

18. The non-transitory computer-readable medium of claim 15, wherein the arrival time is estimated based on real-time data.

19. The non-transitory computer-readable medium of claim 15, wherein the real-time data comprises data from a geographical information system (GIS) service.

20. The non-transitory computer-readable medium of claim 15, wherein the service provider is a taxi driver and the customer is a passenger.