data collection using intelligent agents: when is enough, enough?

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Data collection using Data collection using intelligent agents: intelligent agents: when is enough, enough? when is enough, enough? WISE 2002 WISE 2002 Barcelona, Spain Barcelona, Spain Gove Allen, Jianan Wu Gove Allen, Jianan Wu A. B. Freeman School of Business A. B. Freeman School of Business Tulane University Tulane University New Orleans, Louisiana New Orleans, Louisiana USA USA

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Data collection using intelligent agents: when is enough, enough?. WISE 2002 Barcelona, Spain Gove Allen, Jianan Wu A. B. Freeman School of Business Tulane University New Orleans, Louisiana USA. This Study. Aggregators as Market Surrogates. + Ease of use + Stability of layout - PowerPoint PPT Presentation

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Page 1: Data collection using  intelligent agents:  when is enough, enough?

Data collection usingData collection using intelligent agents: intelligent agents:

when is enough, enough?when is enough, enough?

WISE 2002WISE 2002Barcelona, SpainBarcelona, Spain

Gove Allen, Jianan WuGove Allen, Jianan WuA. B. Freeman School of BusinessA. B. Freeman School of Business

Tulane UniversityTulane UniversityNew Orleans, LouisianaNew Orleans, Louisiana

USAUSA

Page 2: Data collection using  intelligent agents:  when is enough, enough?

 Existing Literature Intelligen

t Agents

# Vendor

s

# Pro-

ducts Product Time#

Obs.

Clay, Kirshnan, and Wolff (2001)Dealtime, PriceScan 32 399 Book

15 month

s161,43

3

Brynjolfsson and Smith (2001)

Dealtime (Evenbette

r) 33 Book

2 month

s1.5

million

Baye, Morgan, and Scholten (2001) Shopper 1000

Elec-tronics

8 month

s4

millionPan, Ratchford, and Shankar (2001)Pan, Ratchford, and Shankar (2002)Shankar, Ratchford, and Pan (2002)Ratchford, Pan, and Shankar (2002) Bizrate 105 581 Various 1 day 6,739

Clemons, Hahn, and Hitt (2002)

8 (no names given) 939

Airline Ticket 4 days 14,024

Pan, Shankar, and Ratchford (2002) Bizrate 905 Various 1 day 905

Ellison and Ellison (2001) Pricewatch 3 7Compu-

ter Parts82

days 968

Baylis and Perloff (2002) C/Net 49 2Elec-

tronics14

weeks 880

Kaufmann and Wood (2000)Mysimon, Dealtime 53 169

Book, CD,

Software38

days123,68123,6800

Addall, Bizrate,Dealtime, ISBN.nu,

Mysimon, PriceGrabber,PriceScan, Shop.Yahoo 81 459 Book

4 month

s2.2

million

This Study

Page 3: Data collection using  intelligent agents:  when is enough, enough?
Page 4: Data collection using  intelligent agents:  when is enough, enough?

Aggregators as Market Aggregators as Market SurrogatesSurrogates + Ease of use+ Ease of use + Stability of layout+ Stability of layout + Profit motivation + Profit motivation + Special access+ Special access + Performance information+ Performance information - Partnerships- Partnerships - Fees- Fees - Decreasing marginal returns- Decreasing marginal returns

Page 5: Data collection using  intelligent agents:  when is enough, enough?

Research QuestionResearch Question

Are there any market representation Are there any market representation biases for aggregators?biases for aggregators?

If there are, what are they?If there are, what are they?

How can researhcers control these How can researhcers control these biases?biases?

Page 6: Data collection using  intelligent agents:  when is enough, enough?

Proposed Metrics Proposed Metrics Vendor Coverage:Vendor Coverage:

Product Coverage:Product Coverage:

Offering Coverage:Offering Coverage:

t trs at time aggregatoion of allound by unproducts fNumber of

me tet i at tigregator sound by agproducts fNumber of T1

t ts at time aggregatoron of all und by univendors foNumber of

e tt i at timregator seund by aggvendors foNumber of T1

t e tors at timl aggregatnion of alfound by uofferings Number of

ime tset i at tggregator found by aofferings Number of T1

Page 7: Data collection using  intelligent agents:  when is enough, enough?

The DataThe Data 8 aggregators8 aggregators

459 books459 books

84 vendors84 vendors

4 months 4 months (3/02 – (3/02 – 6/02)6/02)

2.2 million price observations2.2 million price observations

Parallel, distributed, data collection Parallel, distributed, data collection agent (SECRET Agent)agent (SECRET Agent)

Page 8: Data collection using  intelligent agents:  when is enough, enough?

Aggregator Aggregator SetSet

Vendor Vendor CoverageCoverage

Product Product CoverageCoverage

Offering Offering CoveragCoverag

eeAggregator Aggregator

SetSetVendor Vendor

CoverageCoverageProduct Product

CoverageCoverageOffering Offering

CoverageCoverageAddall Addall 0.42 0.92 0.45 Best 3Best 3 0.86 0.99 0.91

Bizrate Bizrate 0.15 0.92 0.14 Worst 3Worst 3 0.28 0.83 0.23

Dealtime Dealtime 0.24 0.55 0.11 Average 3Average 3 0.59 0.96 0.56

ISBN.NU ISBN.NU 0.13 0.78 0.16 Best 4Best 4 0.91 0.99 0.95

MySimon MySimon 0.51 0.95 0.53 Worst 4Worst 4 0.36 0.90 0.28

PriceGrabber PriceGrabber 0.25 0.70 0.20 Average 4Average 4 0.69 0.98 0.67

PriceScan PriceScan 0.44 0.88 0.49 Best 5Best 5 0.96 0.99 0.97

Yahoo.Shop Yahoo.Shop 0.33 0.83 0.16 Worst 5Worst 5 0.52 0.96 0.34

Best 1Best 1 0.51 0.95 0.53 Average 5Average 5 0.78 0.99 0.76

Worst 1Worst 1 0.13 0.55 0.11 Best 6Best 6 0.99 1.00 0.98

Average 1Average 1 0.31 0.82 0.28 Worst 6Worst 6 0.68 0.98 0.57

Best 2Best 2 0.74 0.99 0.77 Average 6Average 6 0.86 0.99 0.85

Worst 2Worst 2 0.19 0.70 0.19 Best 7Best 7 1.00 1.00 0.99

Average 2Average 2 0.46 0.92 0.44 Worst 7Worst 7 0.84 0.98 0.81

Best 2 > average 5. Best 1 almost as good as worst 6Best 2 > average 5. Best 1 almost as good as worst 6 Average 7Average 7 0.93 0.99 0.93

Page 9: Data collection using  intelligent agents:  when is enough, enough?

Efficient FrontierEfficient Frontier offering coverage (single offering coverage (single

aggregators)aggregators)

Page 10: Data collection using  intelligent agents:  when is enough, enough?

Efficient FrontierEfficient Frontier offering coverage (best and worst offering coverage (best and worst

groups)groups)

Page 11: Data collection using  intelligent agents:  when is enough, enough?

Weighting Metrics Weighting Metrics Product Representativeness:Product Representativeness:

Aggregator Representativeness:Aggregator Representativeness:

Offering Representativeness:Offering Representativeness:

t nion sets in the uaggregatorNumber of

t j at timerom vendorg prices fs reportinaggregatorNumber of T1

t etn the baskproducts iNumber of

me tor j at tior at vendy aggregatound by anproducts fNumber of T1

t ime tdor j at tors at venl aggregatnion of alfound by uofferings Number of

time tendor j atset i at vggregator found by aofferings Number of T1

Page 12: Data collection using  intelligent agents:  when is enough, enough?

Fatbrain.com0.9

9

Product Representativeness

Amazon.com0.8

2

bn.com0.8

0

Half.com0.7

8booksamillion.com

0.74

varsitybooks.com

0.73

bookvariety.com0.7

1

FaithPoint.com0.7

1

powells.com0.7

01bookstreet.com

0.69

bn.com0.7

7Aggregator RepresentativenessAggregator Representativeness

1bookstreet.com0.7

0

powells.com0.6

7

TextbookX.com0.6

5

Amazon.com0.6

4

ecampus.com0.5

9AllBooks4Less.com

0.55

Fatbrain.com0.5

5booksamillion.com

0.50

Half.com 0.48

AggregatorAdda

llBizrat

eDealTim

eISBN.n

uMySimo

nPriceGrabb

erPriceSca

nShop.Yaho

o

Off

ering Representativenes

bn.com0.8

6 0.53 0.25 0.56 0.87 0.67 0.91 0.78

Amazon.com0.7

9 0.75 0.26 0.72 0.83 0.06 0.85 0.011bookstreet.com

0.79 0.68 0.29 - 0.83 0.72 0.89 0.85

powells.com0.8

0 0.52 0.54 0.70 0.01 0.71 0.88 0.86

textbookx.com0.7

9 0.74 0.46 - 0.83 0.69 0.85 0.85

Fatbrain.com0.9

7 - 0.25 0.63 0.99 - 1.00 -

ecampus.com0.7

2 - 0.26 0.56 0.88 0.53 0.88 0.34booksamillion.com

0.92 0.64 - 0.71 - 0.85 0.97 0.01

Half.com0.9

2 - 0.55 0.83 0.97 0.79 - 0.01

Alphacraze.com0.7

0 0.82 - 0.32 - 0.64 0.90 -

Top 10 Vendors by weighting metrics

Page 13: Data collection using  intelligent agents:  when is enough, enough?

Aggregator Biases Aggregator Biases (one randomly selected book and (one randomly selected book and

day)day)AggregatAggregat

ororRangeRange StdStd Std / Std /

Mean Mean (CV)(CV)

Range / Range / MeanMean

Offering Offering CoverageCoverage

AddallAddall $0.00 $0.00 $0.30 $0.30 0.02 0.02 0.02 0.02 0.450.45BizrateBizrate $6.90 $6.90 $1.10 $1.10 0.03 0.03 0.27 0.27 0.140.14DealtimeDealtime $9.42 $9.42 $1.45 $1.45 0.07 0.07 0.44 0.44 0.110.11ISBN.NUISBN.NU $11.40 $11.40 $2.55 $2.55 0.11 0.11 0.51 0.51 0.160.16MySimonMySimon $2.60 $2.60 $0.16 $0.16 0.01 0.01 0.14 0.14 0.530.53PriceGrabbPriceGrabberer

$4.82 $4.82 $0.56 $0.56 0.01 0.01 0.16 0.16 0.20.2

PriceScanPriceScan $2.60 $2.60 $0.01 $0.01 0.00 0.00 0.12 0.12 0.490.49Shop.YahoShop.Yahooo

$10.51 $10.51 $1.98 $1.98 0.09 0.09 0.49 0.49 0.160.16

ISBN: 0791056619 (March 19,2002)

Page 14: Data collection using  intelligent agents:  when is enough, enough?

Aggregator Aggregator BiasesBiases

Page 15: Data collection using  intelligent agents:  when is enough, enough?

Bias Correlation with Bias Correlation with Offering CoverageOffering Coverage

RangeRange StdStd Std / Std / Mean Mean (CV)(CV)

Range / Range / MeanMean

Offering Offering CoveragCoverag

eeRangeRange 1.001.00

StdStd 0.940.94 1.001.00

Std / Mean Std / Mean (CV)(CV)

0.890.89 0.970.97 1.001.00

Range / Range / MeanMean

0.990.99 0.940.94 0.930.93 1.001.00

Offering Offering CoverageCoverage

-0.85-0.85 -0.78-0.78 -0.68-0.68 -0.78-0.78 1.001.00