OPEN EXCHANGE PLATFORMS

• US 20070185779A1
• Filed: 01/31/2007
• Published: 08/09/2007
• Est. Priority Date: 01/31/2006
• Status: Abandoned Application

• Current Assignee: Oath Inc. (Verizon Communications Inc.)
• Original Assignee: Oath Inc. (Verizon Communications Inc.)
• Inventors: O'Kelley, Charles Brian
• Application Number:
  US11/669,716
• Publication Number:
  US 20070185779A1
• Time in Patent Office: Days
• US Class Current: 705/26
• CPC Class Codes: G06Q 30/06 Buying, selling or leasing transactions
• CPC Class Codes: G06Q 30/0601 Electronic shopping [e-shopping]

Abstract

Techniques for identifying a set of business entities eligible to participate in a transaction involving a purchase or sale of a product, commodity or service; generating a graph of the set of business entities using pre-stored information defining relationships between the business entities in the set, each business entity in the set being represented by a node of the graph, each relationship between a pair of identified business entities being represented by an edge of the graph, one of the nodes of the graph being designated as a source node, and one or more of the nodes of the graph being designated as sink nodes; and performing a series of decision processes to identify one of the business entities in the set represented by a sink node to execute the transaction with the business entity represented by the source node.

Claims

1. A computer-implemented method comprising:

identifying a set of business entities eligible to participate in a transaction involving a purchase or sale of a product, commodity or service;

generating a graph of the set of business entities using pre-stored information defining relationships between the business entities in the set, each business entity in the set being represented by a node of the graph, each relationship between a pair of identified business entities being represented by an edge of the graph, one of the nodes of the graph being designated as a source node, and one or more of the nodes of the graph being designated as sink nodes; and

performing a series of decision processes to identify one of the business entities in the set represented by a sink node to execute the transaction with the business entity represented by the source node.

2. The method of claim 1, wherein the performing comprises:

for a particular sink node of the graph, applying a pathing algorithm to determine a path between the source node and the particular sink node.

3. The method of claim 2, wherein the pathing algorithm comprises a shortest path algorithm.

4. The method of claim 2, wherein the path between the source node and the particular sink node passes through no other nodes of the graph.

5. The method of claim 4, wherein:

the transaction involves the purchase of a product, commodity or service;

the source node represents a seller of the product or commodity or a provider of the service; and

the particular sink node represents a potential buyer of the product or commodity or a potential consumer of the service.

6. The method of claim 4, wherein:

the transaction involves the sale of a product, commodity or service;

the source node represents a buyer of the product or commodity or a consumer of the service; and

the particular sink node represents a potential seller of the product or commodity or a potential provider of the service.

7. The method of claim 2, wherein the path between the source node and the particular sink node passes through one or more interior nodes of the graph.

8. The method of claim 7, wherein:

the transaction involves the purchase of a product, commodity or service;

the source node represents a seller of the product or commodity or a provider of the service;

each of the one or more interior nodes represents an intermediary to facilitate the transaction; and

the particular sink node represents a potential buyer of the product or commodity or a potential consumer of the service.

9. The method of claim 7, wherein:

the transaction involves the sale of a product, commodity or service;

the source node represents a buyer of the product or commodity or a consumer of the service;

each of the one or more interior nodes represents an intermediary to facilitate the transaction; and

the particular sink node represents a potential seller of the product or commodity or a potential provider of the service.

10. The method of claim 1, wherein the series of decision processes are performed recursively at the non-sink nodes of the graph, the non-sink nodes comprising the source node and one or more interior nodes.

11. The method of claim 10, wherein each of the series of decision processes comprises a comparison of bid prices associated with nodes directly coupled to the non-sink node at which the decision process is being performed.

12. The method of claim 1, wherein at least one of the decision processes of the series comprises a comparison of at least two bid prices associated with nodes of the graph.

13. The method of claim 12, wherein the at least two bid prices are normalized in accordance with one or more pricing models prior to the comparison.

14. The method of claim 12, wherein the at least two bid prices are normalized in accordance with one or more predictive metrics associated with the commodity or service prior to the comparison.

15. The method of claim 12, wherein the at least two bid prices are associated with nodes of the graph that are children of the node at which the decision process is being performed.

16. The method of claim 1, wherein performing the series of decision processes comprises:

comparing bids associated with nodes of the graph.

17. The method of claim 16, wherein comparing bids comprises:

comparing bids based on one or more of the following metrics;

a priority metric, a normalized price metric, and a percentage delivered metric.

18. The method of claim 1, wherein performing the series of decision processes comprises:

performing a comparison of at least two bids associated with nodes of the graph based on a normalized price metric; and

if the comparison yields a tie result, performing one or more additional comparisons of the at least two bids associated with nodes of the graph based on one or more of the following metrics;

a priority metric and a percentage delivered metric, until a tie-breaking result is yielded.

19. The method of claim 1, wherein performing the series of decision processes comprises:

performing a comparison of at least two bids associated with nodes of the graph based on a normalized price metric; and

if the comparison yields a tie result, randomly selecting one of the at least two bids to yield a result.

20. The method of claim 1, wherein at least one of the decision processes of the series comprises a propagation of information in a direction from the sink nodes to the source node, the information being related to a node that is a child of the node at which the decision process is being performed.

21. The method of claim 1, wherein the business entity in the set identified to execute the transaction is associated with a bid price that yields a highest revenue for the business entity represented by the source node.

22. The method of claim 1, wherein the performing comprises:

determining a payment amount to be paid by the business entity in the set identified to execute the transaction with the business entity represented by the source node.

23. The method of claim 22, wherein the payment amount to be paid is all or a portion of a bid price associated with the business entity in the set identified to execute the transaction.

24. The method of claim 1, wherein the performing comprises:

identifying a first one of the business entities of the set associated with a first bid price that yields a highest revenue for the business entity represented by the source node;

identifying a second one of the business entities of the set associated with a second bid price that yields a second highest revenue for the business entity represented by the source node; and

applying a dynamic pricing reduction rule to the first bid price based on the second bid price to determine a payment amount to be paid by the first one of the business entities of the set, the first one of the business entities being the business entity in the set identified to execute the transaction.

25. The method of claim 24, wherein the payment amount to be paid is the second bid price incremented by a predetermined margin.

26. The method of claim 25, wherein the predetermined margin is expressed as a percentage.

27. The method of claim 24, wherein the payment amount to be paid is greater than a bid price associated with any node within a subtree of the graph in which the first one of the business entities is located.

28. The method of claim 1, wherein each of the business entities in the set satisfies a set of constraints associated with the transaction involving the purchase or sale of the product, commodity or service.

29. The method of claim 28, wherein the set of constraints comprises constraints related to one or more of the following:

price, geography, time of delivery, location of delivery, and quantity.

30. The method of claim 1, further comprising:

receiving information defining a relationship between a first business entity and a second business entity; and

storing the received information.

31. The method of claim 30, wherein the received information comprises information related to a revenue sharing agreement.

32. The method of claim 1, further comprising:

executing the transaction between the identified one of the business entities in the set represented by a sink node with the business entity represented by the source node.

33. The method of claim 32, wherein the executing comprises one or more of the following:

providing sufficient first information to each business entity represented by a node in a path between the source node and the sink node representing the identified one of the business entities in the set to effect the execution of the transaction;

logging sufficient second information to document the execution of the transaction; and

enabling the product, commodity or service to be delivered or provided to the business entity representing the identified one of the business entities in the set.

34. A machine-readable medium that stores executable instructions to cause a machine to:

identify a set of business entities eligible to participate in a transaction involving a purchase or sale of a product, commodity or service;

generate a graph of the set of business entities using pre-stored information defining relationships between the business entities in the set, each business entity in the set being represented by a node of the graph, each relationship between a pair of identified business entities being represented by an edge of the graph, one of the nodes of the graph being designated as a source node, and one or more of the nodes of the graph being designated as sink nodes; and

perform a series of decision processes to identify one of the business entities in the set represented by a sink node to execute the transaction with the business entity represented by the source node.

35. The machine-readable medium of claim 34, wherein the instructions to cause the machine to perform a series of decision processes comprises instructions to perform the series of decision processes recursively at the non-sink nodes of the graph, the non-sink nodes comprising the source node and one or more interior nodes.

36. The machine-readable medium of claim 35, wherein the instructions to cause the machine to perform a decision process of the series comprises instructions to compare bid prices associated with nodes directly coupled to the non-sink node at which the decision process is being performed.

37. The machine-readable medium of claim 34, wherein the instructions to cause the machine to perform a decision process of the series comprises instructions to compare at least two bid prices associated with nodes of the graph.

38. The machine-readable medium of claim 37, wherein the instructions to cause the machine to perform a decision process of the series comprises instructions to normalize the at least two bid prices in accordance with one or more pricing models prior to the comparison.

39. The machine-readable medium of claim 37, wherein the at least two bid prices are associated with nodes of the graph that are children of the node at which the decision process is being performed.

40. The machine-readable medium of claim 34, wherein the instructions to cause the machine to perform the series of decision processes comprises instructions to compare bids associated with nodes of the graph.

41. The machine-readable medium of claim 40, wherein the instructions to cause the machine to compare bids comprises instructions to compare bids based on one or more of the following metrics:

a priority metric, a normalized price metric, and a percentage delivered metric.

42. The machine-readable medium of claim 34, wherein the instructions to cause the machine to perform the series of decision processes comprises instructions to:

perform a comparison of at least two bids associated with nodes of the graph based on a normalized price metric; and

if the comparison yields a tie result, perform one or more additional comparisons of the at least two bids associated with nodes of the graph based on one or more of the following metrics;

a priority metric and a percentage delivered metric, until a tie-breaking result is yielded.

43. The machine-readable medium of claim 34, wherein the instructions to cause the machine to perform the series of decision processes comprises instructions to:

perform a comparison of at least two bids associated with nodes of the graph based on a normalized price metric; and

if the comparison yields a tie result, randomly select one of the at least two bids to yield a result.

44. The machine-readable medium of claim 34, wherein the instructions to cause the machine to perform a series of decision processes comprises instructions to propagate information in a direction from the sink nodes to the source node, the information being related to a node that is a child of the node at which the decision process is being performed.

45. The machine-readable medium of claim 44, wherein the information comprises a bid price.

46. The machine-readable medium of claim 34, wherein the instructions to cause the machine to perform a series of decision processes comprises instructions to determine a payment amount to be paid by the business entity in the set identified to execute the transaction with the business entity represented by the source node.

47. The machine-readable medium of claim 46, wherein the payment amount to be paid is all or a portion of a bid price associated with the business entity in the set identified to execute the transaction.

48. The machine-readable medium of claim 34, wherein the instructions to cause the machine to perform a series of decision processes comprises instructions to:

identify a first one of the business entities of the set associated with a first bid price that yields a highest revenue for the business entity represented by the source node;

identify a second one of the business entities of the set associated with a second bid price that yields a second highest revenue for the business entity represented by the source node; and

apply a dynamic pricing reduction rule to the first bid price based on the second bid price to determine a payment amount to be paid by the first one of the business entities of the set, the first one of the business entities being the business entity in the set identified to execute the transaction.

49. The machine-readable medium of claim 48, wherein the payment amount to be paid is the second bid price incremented by a predetermined margin.

50. The machine-readable medium of claim 48, wherein the predetermined margin is expressed as a percentage.

51. The machine-readable medium of claim 48, wherein the payment amount to be paid is greater than a bid price associated with any node within a subtree of the graph in which the first one of the business entities is located.

52. The machine-readable medium of claim 34, further comprising instructions to cause the machine to:

receive information defining a relationship between a first business entity and a second business entity; and

store the received information.

53. The machine-readable medium of claim 52, wherein the received information comprises information related to a revenue sharing agreement.

54. The machine-readable medium of claim 34, further comprising instructions to cause the machine to:

execute the transaction between the identified one of the business entities in the set represented by a sink node with the business entity represented by the source node.

55. The machine-readable medium of claim 54, wherein the instructions to cause the machine to execute the transaction comprises one or more of the following instructions:

instructions to cause the machine to provide sufficient first information to each business entity represented by a node in a path between the source node and the sink node representing the identified one of the business entities in the set to effect the execution of the transaction;

instructions to cause the machine to log sufficient second information to document the execution of the transaction; and

instructions to cause the machine to enable the product, commodity or service to be delivered or provided to the business entity representing the identified one of the business entities in the set.