Intelligent Personalized Trading Agents that Facilitate

Real-time Decision-makingfor Auctioneers and Buyers in

the Dutch Flower Auctions

Case by Wolfgang Ketter, Eric van Heck, Rob Zuidwijk

Rotterdam School of Management, Erasmus University

Advocate Agents - Slide 3

Dutch Flower Auction Worlds’ largest Association set up by growers

Flower industry is a giant network

– Including: breeders, growers, auctions, wholesalers, retailers, and transportation firms for im- and export.

Import from warmer countries: Israel, Kenya, Zimbabwe etc.

Export to: Germany, UK, France

Advocate Agents - Slide 5

Dutch Flower Auction cont.Retailers

Clock auction

Mediation

Growers WholesalersDutch Flower Auction

Two scenarios:– Push strategy (supply driven) clock auction (70%)

– Pull strategy (demand driven) mediation (30%)

Advocate Agents - Slide 6

Auction Locations DFA has 6 individual auction locations spread

throughout the NL, with a total of 39 auction clocks

Conducts buying transaction

Shipment of goods

Buyer is a retailerwho buys for himself

Client is a retailer

Shipmentof goods

Wholesaler who buys for client

Conducts buying transaction

1st scenario

2nd scenario

Advocate Agents - Slide 7

Clock Auction Flowers transported from cold-storage

warehouse to auction hall on carts.

2-3 clocks per hall.

Sample shown to bidders by ‘raiser’.

Buyers bid using Dutch auction: price starts high and drops fast. First person to stop the clock wins and pays that price. Invented in 1887.

Extremely fast! On average an auction clears every 3-5 seconds.

Advocate Agents - Slide 8

Clock Auction cont.

Advocate Agents - Slide 9

Clock Auction cont. One lot is divided among many commercial transactions

– Lot: is the supply of flowers from one grower

– Commercial transactions (sub lots): are different portions of one lot sold to different buyers

Units for sale Price Quantity Buyer

25 15 ct 5 H. De Jager

20 14 ct 6 T.H. Pietersen

14 18 ct 4 P.J. De Vries

10 13 ct 5 A. Jansen

5 12 ct 5 A. B. De Groot

1 lo

t

5 c

om

me

rcia

l tran

sa

ctio

ns

or s

ub

lots

E.g. 1 lot below is divided into 5 commercial transactions.

Advocate Agents - Slide 10

1

2

5

4

6

3

X

7

8

0

10

20

30

40

50

60

70

80

90

10

9

Name Example values

1.        Producer Mr. Z. Boon

2.        Product Tulips, roses etc.

3.        Unit of currency Cents, 5 cents, 10 cents, Euro’s etc.

4.        Buyer Mr. S. Klaasen

5.        Units  

6.        Number per unit Amount of stems per unit

7.      Minimum purchase quantity

 

8.        Negative comment on quality

“Nice leaves”

9.        Positive comment on quality

“Small water stains”

10.     Quality indication A1 (highest quality), A2, B1, B2 (lowest quality)

10

2

Advocate Agents - Slide 11ProductsUnits

(= wagons x units per wagon)

Wagons Units per trolley

Amount of stems per unit

S1, S2, S3, and S4 are sorting methods

S1 = lengthS2 = weight, or diameter

S3 & S4 are dependent on the traded flower

Negative comments

Positive comments

Grower(seller)

Clock

Lot nr. Unit of currency

Amount of stems per

unit

Units

Minimum purchase quantity

Identification number of

the auctioned goods

InformationSub lot nr.

Advocate Agents - Slide 12

Information

Flower type and quality (including pictures and videoclip) Seller (name, background, reputation) Auction clock (price, units) Buyer (identification) Previous transactions Services (logistics, payment, settlement)

– Different buyers have different information needs…

Advocate Agents - Slide 13

Buyer Profiles 1. General wholesaler (cost driven exporter)

2. Specialist wholesaler (differentiator on quality)

3. Large retailer (medium quality retailer)

4. Small retailer (flower shop with specific client wishes)

Competing in different markets => different information needs

Information needed for decision making

– Price information

– Product information

– Transportation information

Advocate Agents - Slide 14

Decision Parameters (1) price (2) product, including quality (3) transportation costs (4) transportation time (5) upcoming auctions (6) market conditions

– More?

Based on this information, must choose price and quantity in about 4 seconds

Advocate Agents - Slide 15

Auctioneer Profile

Auctioneer governs clock trading process, by controlling five parameters

– Speed of clock

– Initial price

– Swingback

– Reserve price

– Minimum lot size

Speed vs. price tradeoff

Advocate Agents - Slide 16

Decision Parameters (1) historical prices (2) quality measures (3) upcoming auctions (4) market conditions

– More?

Based on this information, must make 5 decisions in about 4 seconds

Advocate Agents - Slide 17

Intelligent Software Agents

An agent is anything that:– perceives its environment through sensors – acts autonomously upon that environment through

effectors. A human agent

– Sensors: eyes, ears etc. – Effectors: body parts as hands and legs.

Advocate Agents - Slide 18

Intelligent Software Agents

Intelligent software agents are used for complex decision-making

Intelligent agents monitor the environment, make internal calculations, and act (or recommend actions) autonomously.

Useful for supporting trade at auctions.

E.g. for eBay auctions there are “auction bots”.

Advocate Agents - Slide 19

Example of Ebay auction agent You define your preferences (personalize) and

the agent monitors auctions and buys (acting autonomously) for you.

Advocate Agents - Slide 20

Case Conclusion Case Question:

How can personalized intelligent agents be used at the DFA to enable better decisions for the bidders and auctioneers?

Guiding question: Do agents bring a saving in costs, or a true competitive advantage?

Advocate Agents - Slide 21

Dutch Flower Auction CaseYou might want to explore…

www.floraholland.com (DFA website) Auction bidding software

– www.jbidwatcher.com– www.freedownloadscenter.com/Best/auction-

bidding.html Chapter 2 of Artificial Intelligence: A Modern Approach

by Russell and Norvig, 1995. Maes et al., 1999. Agents that Buy and Sell