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Why Beauty Matters An Experimental Investigation

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Why Beauty Matters An Experimental Investigation Powered By Docstoc
					   Social Learning and
   Consumer Demand
Markus Mobius (Harvard University and NBER)
Paul Niehaus (Harvard University)
Tanya Rosenblat (Wesleyan University and IAS)

                     April 2006
Motivation
We want to study social learning in the context of how consumer
    preferences form.

   How strong are social learning effects absolutely and
    relatively compared to informative advertising?

   How strong are social influence effects (on valuations)
    absolutely and relatively compared to persuasive
    advertising?

   Which agents are influential?
       Learning                            Persuasion
 Strong Social Learning




Agents communicate directly about the product, sharing factual
information:
    “I didn’t buy it because it’s not Mac compatible”
    “I’ve heard Sony makes the most reliable ones”
    “They have a lot of vegetarian dishes on the menu”
      Learning                          Persuasion
Strong Social Learning

Weak Social Learning


Agents observe their friends’ consumption decisions and enjoyment
of products and make inferences about the products’ attributes.


       “Greg got one for Christmas and I know he really liked it”


These inferences should be sharper when friends know their friend’s
preferences well.
      Learning                           Persuasion
Strong Social Learning                    Social Influence

Weak Social Learning




Agents observe their friends’ consumption decisions and....
    • Their private tastes are altered
    • The status value of consuming the product is altered
      Learning                           Persuasion
Strong Social Learning                    Social Influence

Weak Social Learning                 Persuasive Advertising

Informative Advertising




Agents observe advertising for the product. They may learn about
objective features of the product or be persuaded to like it or be
persuaded of its prestige value.
Methodology: basic paradigm

Stage 1: Measure the network (Harvard
         Undergraduates)


Stage 2: Distribute actual products and
         track social learning
Methodology



 Measuring the Social Network
Measuring the Network
 Rather than surveys, agents play in a trivia
  game
 Leveraged popularity of
  www.thefacebook.com
      Membership          rate at Harvard College over
       90% *
      95% weekly return rate *


* Data provided by the founders of thefacebook.com
                                                                                         home     search    global   social net   invite   faq   logout

                                         Paul Niehaus' Profile (This is you)                                                                              Har

                   quick search go
                                          Picture                             [ edit ]   Information                                                      [ ed
                                                                                         Account Info:
                My Profile [ edit ]

• Markus        My Friends
                My Groups
                My Parties
                                                                                         Name:
                                                                                         Member Si nce:
                                                                                                                 Paul Niehaus
                                                                                                                 May 18, 2004
                                                                                         Last Update:            June 6, 20 05
                My Messages                                                              Basic Info:                                                      [ ed
                My Account
                My Pri vacy                                                              School:                 Harvard '04
                                                                                         Geography:              Boston, MA
                                                                                         Status:                 Grad Student


• His Profile          sponsor
                                                                                         Sex:
                                                                                         Concentratio n:
                                                                                                                 Male
                                                                                                                 Econom ics
                Work from bed!              Visualize My Friends                         Birthday:               03/11/1982
                (Or desk, or kitchen)                                                    High Scho ol:           St. John's Prep '00
                                            Edit My Profile
                                                                                         Contact Inf o:                                                   [ ed
                Write short abstracts       My Account Prefer ences
                                                                                         Email:
                and earn roya lties         My Privacy Preferences
                                                                                         Screenname:             pfn007


• (Ad Space)    www.shvoong .com                                                         Mobile:                 508.335.5242
                                          Connection                                     Website:                http://www.people.fa s.harvard.edu/~ nieha
                                                         This is you.                    Personal Info:                                                   [ ed
                • offensive? t ell us.
                • announce something                                                     Relationship Status: In a Relat ionship with
                                          Access                                                                 Lauren Young (Berkel ey)
                                          Paul is currently l ogged in from a non-       Interests:              visiting / talking to / daydreaming about
                                          residential location.                                                  Lauren Young
                                                                                         Clubs an d Jobs:        Americans for Being Awesome
                                          Friends at Harvard                  [ edit ]   Favorite Musi c:        donkey kong count ry II soundtrack
                                                                                         Favorite Books:         The Bible, Development a s Freedom, LOTR
                                                                                                                 The Screwtape Letters , Moneyb all, MWG!

• His Friends                                                                            Favorite Movi es:       Kindergarten Cop , Office Space , Friday ,
                                                                                                                 Good Will Hunt ing, Pumping Iron 20th
                                                                                                                 annivers ary edition , pretty much any othe r
                                                                                                                 movies with Ahnold except Junior, Dr.
                                              Rohit                        Russell
                                                          Anna Byrne                                             Strangelo ve, Kujo's happy bi rthday movie
                                             Chopra                        Anello
                                                                                         Favorite Quote :        good advic e I have rece ived fro m friends:

                                                                                                                 "it'll be snowy and cold tomorrow, so kee p
                                                                                                                 warm and avoi d slipperiness."
                                                                                                                 - Yi Qian
Trivia Game: Recruitment
1.   On login, each Harvard undergraduate
     member of thefacebook.com saw an invitation
     to play in the trivia game.
2.   Subjects agree to an informed consent form –
     now we can email them!
3.   Subjects list 10 friends about whom they want
     to answer trivia questions.
4.   This list of 10 people is what we’re interested
     in (not their performance in the trivia game)
Trivia Game: Trivia Questions
1.   Subjects list 10 friends – this creates
     10*N possible pairings.
2.   Every night, new pairs are randomly
     selected by the computer
    Example: Suppose Markus listed Tanya
     as one of his 10 friends, and that this
     pairing gets picked.
Trivia Game Example
a)   Tanya (subject) gets an
     email asking her to log in
     and answer a question
     about herself
b)   Tanya logs in and answers,
     “which of the following kinds
     of music do you prefer?”
Trivia Game Example (cont.)
c)   Once Tanya has answered,
     Markus gets an email inviting
     him to log in and answer a
     question about one of his
     friends.
d)   After logging in, Markus has 20
     seconds to answer “which of
     the following kinds of music
     does Tanya prefer?”
Trivia Game Example (cont.)
e)   If Markus’ answer is correct, he and
     Tanya are entered together into a nightly
     drawing to win a prize.
Trivia Game: Summary
   Subjects have incentives to list the 10 people they are
    most likely to be able to answer trivia questions about
   This is our (implicit) definition of a “friend”
   This definition is suited for measuring social learning
    about products.
   Answers to trivia questions are unimportant
       ok if people game the answers as long as the people it’s easiest
        to game with are the same as those they know best.
       Roommates were disallowed
       20 second time limit to answer
       On average subjects got 50% of 4/5 answer multiple choice
        questions right – and many were easy
Recruitment
   In addition to invitations on login,
     Posters   in all hallways
     Workers in dining halls with laptops to step through
      signup
     Personalized snail mail to all upper-class students
     Article in The Crimson on first grand prize winner

   Average acquisition cost per subject ~= $2.50
Network Data
   23,600 links from participants
   12,782 links between participants
   6,880 of these symmetric (3,440 coordinated friendships)
       Similar to 2003 results
   Construct the network using “or” link definition
       5576 out of 6389 undergraduates (87%) participated or were
        named
   One giant cluster
   Average path length between participants = 4.2
   Cluster coefficient for participants = 17%
       Lower than 2003 results – because many named friends are in
        different houses
Number of Roommate links, friend (N1), indirect
friend (N2), and friends of distance 3 (N3) for an
average subject (OR network on all participants of
trivia game)
Type of Link       Number of        Ratio
                   Links
Roommate           .96              1

N1               7.68             8

N2               57.91            60.32

N3               347.14           361.6
Methods in Comparison
   2003 House Experiment in 2 undergraduate
    houses

   Email-data: Sacerdote and Marmaris (QJE
    2006)

   Mutual-friend methods with facebook data?
    (Glaeser et al, QJE 2000)
Methodology



     Seeding Information
Seeding Information
       1.       Elicit subjects’ initial valuations
                  Center empirical estimates
                  Decompose valuations (hedonics)
       2.       Randomized treatments
                  Distribute product samples
                  Information / instructions
       3.       Randomized advertising
                  Print (Crimson) and online
                   (thefacebook.com)
                  Informative and persuasive
       4.       Elicit subjects’ final valuations
Example
   A hypothetical subject “Paul” might be exposed
    to the following treatments:
    A  friend of Paul’s of social distance 2 used a PDA
     The friend was told about the PDA’s instant
      messenger capabilities
     Paul saw an advertisement for the PDA in the
      newspaper that emphasized it’s hip-ness
     Paul did not see online advertising for the PDA
Product Samples
 We want new products to maximize the
  potential for social learning.
 Want to vary products by
     Likely demographic appeal
     Potential for strong learning (need a manual?)
     Potential for weak learning and social
      influence – the “buzz factor”
Durables
                        T-Mobile Sidekick II




    Philips Key019
    Digital Camcorder



                             Philips ShoqBox
Perishables                 Student Advantage
                            Discount Card




                      Baptiste Studios
                      Yoga Vouchers




Qdoba Meal Vouchers
Step I: Elicit Valuations
   We want to elicit valuations for a product without
    telling subjects what the product is.

   Our solution: We treat a product as a vector of
    attributes which span a space containing the
    specific product.

   We can elicit valuations for each attribute
    without revealing product.
Step I: Configurators
   Familiar examples with posted menus of
    prices
     many computer manufacturers (e.g. Dell)
     some car manufacturers

   Here, subjects bid for features
     Baselinebid for “featureless” product
     Incremental bids for distinct features
Constructed Bids
   Subjects told that either this bid or their bid in the
    followup will be entered into a uniform-price
    auction with equal probability
   Construction:




   Incentives: bid as accurately as possible
   Extension: interactions between features
   Feature descriptions                           Feature bids

Potential additional features
for this product include:                    Textbook discounts

                                                     6
 Amtrak discounts: student                                                          Baseline bid
 discounts on Amtrak trains.
                                Clothing discounts

 Textbook discounts: on                 12
 textbook purchases at
 Barnes&Noble.com


 Greyhound discounts:
 student discounts on                             Baseline bid for Student                     Greyhound discounts
 Greyhound trains.                                Discount Card
                                                                                                      0
 Online guides: website                                      14
 provides a guide to
 discounts by product type
 and by city.                                                                          Amtrak discounts

                                                                                              0
 Clothing discounts: student
 discounts at Urban
 Outfitters.                                                        Online guides

                                                                             0
                        Distributions of Imputed Bids
      300
      250
      200
      150
$

      100
      50
      0
      -50




              Card    Yoga     Food    Camcorder   ShoqBox   Sidekick
    (Price)   ($20)   ($50)    ($35)    ($150)      ($150)    ($250)
Distributions of Imputed Bids
   Results from configurators look sensible
     In each case, market prices lie between
      median bid and upper tail
     T-Mobile and Philips confirmed that demand
      curves for their products are similar to results
      from more traditional analysis
Step 2: Randomized Product Trials

   Perishables
    ½   year Student Advantage cards
     5 yoga vouchers
     5 meal vouchers

   Durables
     Try  out for approximately 4 weeks during end
      of term
Randomization
   Blocked by year of graduation, gender,
    and residential house

   Email invitations to come pick up samples

   Invitation times varied to vary strength of
    exposure (April 26th – May 3rd)
Info Treatments
   Varied information communicated verbally by
    workers doing distribution
   Information treatments correspond to product
    features in our configurators (5 or 6 features for
    each product).
   Reinforced this information treatment with
    reminder emails
   Each treatment given with 50% probability to
    each subject
“Buzz” Treatments
   Product-specific treatments without information
    content
   Intended to increase subject’s enjoyment of the
    product
   Examples
     Subway   tokens for yoga, Qdoba
     5 free MP3s on ShoqBox
     Extra pre-paid balance on Sidekicks
     Special one-store subsidy on Student Advantage
      cards
   Given with 50% probability to each subject
                                                                                                         home     search    global



Step 2: Advertising                quick search go
                                                         Paul Niehaus' Profile (This is you)


                                                          Picture                             [ edit ]   Information
                                                                                                         Account Info:
                                My Profile [ edit ]
                                My Friends                                                               Name:                   Pau
                                My Groups                                                                Member Si nce:          Ma


Online Advertising              My Parties
                                My Messages
                                My Account
                                My Pri vacy
                                                                                                         Last Update:
                                                                                                         Basic Info:
                                                                                                         School:
                                                                                                                                 Jun


                                                                                                                                 Ha
                                                                                                         Geography:              Bos
                                                                                                         Status:                 Gra

   Delivered via                      sponsor
                                                                                                         Sex:
                                                                                                         Concentratio n:
                                                                                                                                 Ma
                                                                                                                                 Eco

    thefacebook.com             Work from bed!
                                (Or desk, or kitchen)
                                                            Visualize My Friends
                                                            Edit My Profile
                                                                                                         Birthday:
                                                                                                         High Scho ol:
                                                                                                         Contact Inf o:
                                                                                                                                 03/
                                                                                                                                 St.

                                Write short abstracts       My Account Prefer ences

   Mixed in with normal paid   and earn roya lties         My Privacy Preferences
                                                                                                         Email:
                                                                                                         Screenname:
                                                                                                         Mobile:
                                                                                                                                 pfn
                                                                                                                                 508
                                www.shvoong .com
    advertising                 • offensive? t ell us.
                                                          Connection
                                                                         This is you.
                                                                                                         Website:
                                                                                                         Personal Info:
                                                                                                                                 htt


                                • announce something                                                     Relationship Status: In

   65% of subjects saw ads                               Access
                                                          Paul is currently l ogged in from a non-       Interests:
                                                                                                                                 Lau
                                                                                                                                 vis
                                                          residential location.                                                  Lau

   232,736 impressions                                   Friends at Harvard                  [ edit ]
                                                                                                         Clubs an d Jobs:
                                                                                                         Favorite Musi c:
                                                                                                         Favorite Books:
                                                                                                                                 Am
                                                                                                                                 don
                                                                                                                                 Th

    (approx. 300 per treated                                                                             Favorite Movi es:
                                                                                                                                 Th
                                                                                                                                 Kin
                                                                                                                                 Go

    subject)                                                  Rohit
                                                                          Anna Byrne
                                                                                           Russell
                                                                                                                                 ann
                                                                                                                                 mo
                                                                                                                                 Str
                                                             Chopra                        Anello

   136 clicks (in line with                                                                             Favorite Quote :        goo

                                                                                                                                 "it'
                                                                                                                                 wa
    averages)                                                                                                                    -Y

                                                                                                                                 "yo
                                                                                                                                 wo
                                                                                                                                 -M

                                                                                                                                 "go
                                                            Shann on                       Daniel                                -E
                                                                          Zach Lazar
                                                            Christmas                      Morales
Advertising
Content
   Content from sponsor
    companies
   Tweaked to vary
    informational content
    in line with product
    features
   Also non-informative
    versions
Step 2: Advertising
Print Advertising
 Inlets in The Crimson, Harvard’s student
  newspaper
 One of nation’s largest student papers,
  daily readership approx. 14,000
 Delivered to undergrad students’ rooms
 Inlets allow randomization across
  residential houses
All ads for a product has the same style
and differed only in the informational content.
Print advertising
   4 inlets with two ads each.


   3 ads emphasizing a single feature of a product.


   Residents in a house were exposed to either 2
    or 3 impressions of the same print ad.
Step 4: Final Valuations
   Subjects receive full product descriptions and
    submit a second round of bids, which go into the
    auctions with 50% probability
   Subjects also…
     Predict what the average bid will be
     Predict what a sample of their friends will bid in the
      auction
     Answer factual questions about each product
     Indicate their confidence in these answers
                       Facebook Experiment
                          First Product

                                     Personal Sound System
                                        with MP3 players
                                                                           Time left: 46
                                         This product is a Personal Sound System,
                                      an MP3 player with two inbuilt speakers loud
                                      enough to fill a room. It is small enough to fit
                                      in your pocket and you can upload songs
                                      directly from your computer.




                                            Please submit your bid for this product:
                                          ___    Dollars


                                      You can increase your earnings by 50 cents if your
                                      answer to the following question is not more than
                                      10 percent off.

                                         What is your best guess for the average
                                      bid of all other participants?: ___  Dollars


Next Page >>   1   2      3      4          5            6            7             8
                                           Facebook Experiment
                                                     First Product

            Personal Sound System with MP3 players
For each of the following students please predict how they will bid in the auction. For each student if your answer is within
10 percent of their true bid we will add 10 cents to your earnings.




      Danielle Sassoon (FR, Canaday)           ___       Dollars       Skyler Johnson (FR, Canaday)        ___   Dollars




      Rachel Thornton (FR, Canaday)            ___       Dollars       Danny Mou (FR, Canaday)             ___   Dollars




 Next Page >>          1             2               3             4           5           6           7            8
Eliciting Confidence Levels
                 Meet “Bob the Robot” and his
                  clones Bob 1 – Bob 100
                 Subjects are randomly paired with
                  an (unknown) Bob
                 Subjects indicated a “cutoff Bob” at
                  which they are indifferent about
                  who should answer the question
                 If assigned Bob is better than the
                  cutoff, Bob answers the question;
                  otherwise we use subject’s answer
                 Incentive-compatible mechanism to
                  elicit subject’s belief that he/she will
                  get the question right
                       Facebook Experiment
                         Second Product

                                     T-Mobile Sidekick II
                                                                                         Time left: 36
                           How confident are you that you can answer some YES/NO
                         questions about this product correctly?
                         Your confidence: ___     percent




                         You can increase your earnings by 50 cents if your answer to the following
                         question is not more than 10 percent off.

                            Please estimate the average confidence of other participants in this
                         study to answer some YES/NO question about this product correctly?
                          ___    percent




Next Page >>   1   2       3              4             5             6              7                8
                                   Facebook Experiment
                                         Second Product

                               T-Mobile Sidekick II
                                                                                                 Time left: 84
                 Does the Sidekick include AOL messenger?                 Your confidence:
    Question 1
                    YES     NO                                             ___   percent



                 Does the Sidekick have a color screen?                   Your confidence:
    Question 2
                    YES     NO                                             ___   percent



                 Does the Sidekick have 10 or more hours of battery
                                                                          Your confidence:
    Question 3   life?
                                                                           ___   percent
                     YES    NO



                 Does the Sidekick have a QWERTY keyboard?                Your confidence:
    Question 4
                    YES     NO                                             ___   percent



                 Does the Sidekick include a camera?                      Your confidence:
    Question 5
                    YES     NO                                             ___   percent



                 Does the Sidekick use the Pocket PC OS?                  Your confidence:
    Question 6
                    YES     NO                                             ___   percent




Next Page >>     1            2            3              4           5            6         7         8
Analysis



           Measuring Learning
Analysis
   Stage I: Check whether info and ad
    treatments affected a subject’s
    knowledge.




   Stage II: Use info treatments as
    instruments to measure social learning.
Analysis
   Stage I: Check whether info and ad
    treatments affected a subject’s
    knowledge.
       Product Group (PG) – Likelihood of answering a question
        about a feature correctly if primed about that feature at
        distribution
       Non-Product Group (NPG) – Likelihood of answering a
        question about a feature correctly if exposed to informative
        advertising about that feature
Stage I: Effect of Info Treatments on
Knowledge (PG)
Stage I: Effect of Info Treatments on
Knowledge (PG)
                               94.2
          85.2
Stage I: Effect of Info Treatments on
Knowledge (PG)
                                                94.2
          85.2




        Subjects who received a product and were primed on a
        Feature are about 9% more likely to answer the question
        about the feature correctly.
 Stage I: Info-Treatments
                          FCONFIDENCE                     FCORRECTANSWER
                    (1)        (2)       (3)        (4)         (5)        (6)


NUMTREATED           .748*      .766                   .007        .007
                    (.373)    (.505)                 (.007)      (.007)


FTREATED            7.057*    7.087*      7.080*     .082**      .083**     .085**
                     (.825)    (.825)      (.825)    (.015)      (.014)     (.014)


Intercept          85.468* 85.361*       85.645*     .838**      .837**     .856**
                    (1.065) (1.065)       (1.065)    (.019)      (.021)     (.010)


Fixed effects       None         RE            FE    None             RE         FE
N                    1927      1927        1927       1930        1930       1930
R2                    .054      .056        .058      .022        .023       .022
Significance Levels: *: 5%      **: 1%
 Stage I: Info-Treatments
                          FCONFIDENCE                     FCORRECTANSWER
                    (1)        (2)       (3)        (4)         (5)        (6)


NUMTREATED           .748*      .766                   .007        .007
                    (.373)    (.505)                 (.007)      (.007)


FTREATED            7.057*    7.087*      7.080*     .082**      .083**     .085**
                     (.825)    (.825)      (.825)    (.015)      (.014)     (.014)


Intercept          85.468* 85.361*       87.645*     .838**      .837**     .856**
                    (1.065) (1.065)       (1.065)    (.019)      (.021)     (.010)


Fixed effects       None         RE            FE    None             RE         FE
N                    1927      1927        1927       1930        1930       1930
R2                          knowledge.058
       Both confidence and .056
                   .054                         with
                                      increases .022 info treatments. .022
                                                            .023
Significance Levels: *: 5%      **: 1%
Stage I: Effect of Online Ad on Knowledge
(NPG)




Effect of online ads on subjects who did not receive products or print ads.
Stage I: Effect of Online Ad on Knowledge
(NPG)
                                       73.5 %                   71.0 %
               64.7 %




Effect of online ads on subjects who did not receive products or print ads.
Stage I: Effect of Online Ad on Knowledge
(NPG)
                                       73.5 %                   71.0 %
               64.7 %




              Subjects who received online ads are about 5-8% more
              likely to answer the question about the feature correctly.




Effect of online ads on subjects who did not receive products or print ads.
Stage I: Effect of Print Ad on Knowledge
(NPG)




Effect of print ads on subjects who did not receive products or online ads.
Stage I: Effect of Print Ad on Knowledge
(NPG)
                                                               79.8%
                                       71.3%
                64.8%




Effect of print ads on subjects who did not receive products or online ads.
Stage I: Effect of Print Ad on Knowledge
(NPG)
                                                                79.8%
                                       71.3%
                64.8%




               Subjects who received print ads are about 8-15% more
               likely to answer the question about the feature correctly.
               The effect is increasing in intensity of exposure.




Effect of print ads on subjects who did not receive products or online ads.
     Stage I: Ad-Treatments
                                       FCONFIDENCE                   FCORRECTANSWER
                                 (1)         (2)        (3)        (4)        (5)       (6)

PIMPRESSIONS                    1.108        1.142               -.022#      -.022
                                (.698)     (1.133)               (.012)     (.014)

FIMPRESSIONS                     2.278      2.198*     2.182*    .121**     .121**    .120**
                               (1.525)     (1.075)    (1.075)    (.026)     (.026)    (.025)


PCRIMSONNUMADS                 -.520**      -.496*              - .008**   - .008**
                                (.146)      (.243)                (.003)     (.003)

FCRIMSONNUMADS                 1.883**     1.659**    1.614**    .052**     .051**    .048**
                                (.264)      (.187)     (.187)    (.005)     (.004)    (.004)

Intercept                  63.496**       63.509**   63.144**    .650**     .650**    .640**
                            (0.249)        (0.439)    (0.138)    (.004)     (.005)    (.003)

Fixed effects                   None           RE         FE     None          RE        FE

N                              22,959      22,959     22,959    22,995     22,995     22,995

R2                               .003        .003       .004       .006       .007      .008
Significance Levels:   #:10%      *: 5%    **: 1%
     Stage I: Ad-Treatments
                                       FCONFIDENCE                   FCORRECTANSWER
                                 (1)         (2)        (3)        (4)        (5)       (6)

PIMPRESSIONS                    1.108        1.142               -.022#      -.022
                                (.698)     (1.133)               (.012)     (.014)

FIMPRESSIONS                     2.278      2.198*     2.182*    .121**     .121**    .120**
                               (1.525)     (1.075)    (1.075)    (.026)     (.026)    (.025)


PCRIMSONNUMADS                 -.520**      -.496*              - .008**   - .008**
                                (.146)      (.243)                (.003)     (.003)

FCRIMSONNUMADS                 1.883**     1.659**    1.614**    .052**     .051**    .048**
                                (.264)      (.187)     (.187)    (.005)     (.004)    (.004)

Intercept                  63.496**       63.509**   63.144**    .650**     .650**    .640**
                            (0.249)        (0.439)    (0.138)    (.004)     (.005)    (.003)

Fixed effects                   None           RE         FE     None          RE        FE

N                              22,959      22,959     22,959    22,995     22,995     22,995

R2                          and
            Both confidence.003 knowledge increases with ad treatments.
                                   .003    .004          .006     .007                  .008
Significance Levels:   #:10%      *: 5%    **: 1%
 Stage I: Buzz-Treatments
                                       BID
                            All        Services       Gadgets
                       Products


BUZZ                      8.504*           1.516      23.706*
                         (4.206)         (1.561)      (9.176)


NUMTREATED                3.780*               .822     5.837*
                         (1.886)             (.669)    (4.526)




N                            373               227        146
R2                           .019              .01       .048
Significance Levels: *: 5%    **: 1%
 Stage I: Buzz-Treatments
                                            BID
                            All              Services            Gadgets
                       Products


BUZZ                      8.504*                 1.516           23.706*
                         (4.206)               (1.561)           (9.176)


NUMTREATED                3.780*                    .822           5.837*
                         (1.886)                  (.669)          (4.526)

                 Buzz treatments raise valuations for gadgets.

N                            373                    227              146
R2                           .019                   .01             .048
Significance Levels: *: 5%    **: 1%
Analysis: stage II
 Use successful first stage as instruments
  for measuring the effects of social
  learning.
 Regress confidence or correct answers of
  every NPG member on sum friends’
  knowledge (PG) at various social distance
  using sum of info treatments as
  instruments.
Confidence
                                                                FCONFIDENCE
                                                       (1)                        (2)

PGFCONFIDENCE_R                                         .064*                    .057#
                                                       (.029)                   (.031)

PGFCONFIDENCE_NW1                                      .040**                    .034*
                                                       (.013)                   (.014)

PGFCONFIDENCE_NW2                                        .005                    .008#
                                                       (.005)                   (.005)

PGFCONFIDENCE_NW3                                      .003**                   .009**
                                                       (.001)                   (.001)

Control for # of Eligible                                NO                      YES

Intercept                                            59.628**                 67.870**
                                                       (.826)                  (1.197)

N                                                      8,982                    8,982

R2                                                     0.018                    0.045

Significance Levels:        #:10%   *: 5%   **: 1%
FCONFIDENCE
                                                                FCONFIDENCE
                                                       (1)                        (2)

PGFCONFIDENCE_R                                         .064*                    .057#
                                                       (.029)                   (.031)

PGFCONFIDENCE_NW1                                      .040**                    .034*
                                                       (.013)                   (.014)

PGFCONFIDENCE_NW2                                        .005                    .008#
                                                       (.005)                   (.005)

PGFCONFIDENCE_NW3                                      .003**                   .009**
                                                       (.001)                   (.001)

Control for # of Eligible                                NO                      YES

Intercept                                            59.628**                 67.870**
                                                       (.826)                  (1.197)

N                                                      8,982                    8,982

R2                                                     0.018                    0.045

Significance Levels:        #:10%   *: 5%   **: 1%
FCONFIDENCE
                                                                   FCONFIDENCE
                                                       (1)                           (2)

PGFCONFIDENCE_R                                         .064*                       .057#
                                                       (.029)                      (.031)

PGFCONFIDENCE_NW1                                     .040**                        .034*
                                                      (.013)                       (.014)

PGFCONFIDENCE_NW2                                        .005                       .008#
                                                       (.005)                      (.005)

PGFCONFIDENCE_NW3                                     .003**                       .009**
                                                      (.001)                       (.001)

Control for # of Eligible                                NO                         YES

Intercept                                            59.628**                     67.870**
Control for # of subjects who were eligible          to(.826)
                                                         receive   products at     (1.197)
                                                                                 distance
R, NW1, NW2 and NW3.
N                                                      8,982                       8,982

R2                                                     0.018                       0.045

Significance Levels:        #:10%   *: 5%   **: 1%
FCORRECTANSWER
                                                              FCORRECTANSWER
                                                     (1)                         (2)

PGFCORRECTANSWER_R                                   .108**                     .070*
                                                     (.026)                    (.030)

PGFCORRECTANSWER_NW1                                 .041**                      .018
                                                     (.013)                    (.014)

PGFCORRECTANSWER_NW2                                 .019**                    .020**
                                                     (.005)                    (.005)

PGFCORRECTANSWER_NW3                                 .007**                    .018**
                                                     (.001)                    (.002)

Control for # of Eligible                              NO                       YES

Intercept                                            .567**                0.696**
                                                     (.010)                (0.014)

N                                                    9,006                     9,006

R2                                                   0.033                     0.064

Significance Levels:        #:10%   *: 5%   **: 1%
FCORRECTANSWER
                                                              FCORRECTANSWER
                                                     (1)                         (2)

PGFCORRECTANSWER_R                                   .108**                     .070*
                                                     (.026)                    (.030)

PGFCORRECTANSWER_NW1                                 .041**                      .018
                                                     (.013)                    (.014)

PGFCORRECTANSWER_NW2                                 .019**                    .020**
                                                     (.005)                    (.005)

PGFCORRECTANSWER_NW3                                 .007**                    .018**
                                                     (.001)                    (.002)

Control for # of Eligible                              NO                       YES

Intercept                                            .567**                0.696**
                                                     (.010)                (0.014)

N                                                    9,006                     9,006

R2                                                   0.033                     0.064

Significance Levels:        #:10%   *: 5%   **: 1%
FCORRECTANSWER
                                                              FCORRECTANSWER
                                                     (1)                         (2)

PGFCORRECTANSWER_R                                   .108**                     .070*
                                                     (.026)                    (.030)

PGFCORRECTANSWER_NW1                                 .041**                      .018
                                                     (.013)                    (.014)

PGFCORRECTANSWER_NW2                                 .019**                    .020**
                                                     (.005)                    (.005)

PGFCORRECTANSWER_NW3                                 .007**                    .018**
                                                     (.001)                    (.002)

Control for # of Eligible                              NO                       YES
One standard deviation increase in each friend’s knowledge (about 30%)
raises my knowledge by 1% to 2%.
 Intercept                                  .567**                0.696**
The total effect is about 9% because subjects are influenced by several
                                            (.010)                 (0.014)
treated subjects on average.
N                                                    9,006                     9,006

R2                                                   0.033                     0.064

Significance Levels:        #:10%   *: 5%   **: 1%
Alternative approach:
   Regressing knowledge on friends’ knowledge only measures average
    amount of social learning.

   We can instead measure social learning conditional on two subjects having
    reported to have talked to each other (collected during follow-up – 350
    NPG subjects listed specific PG subjects whom they had talked to).

   We exploit the fact that we both randomly distributed products and
    randomized information for each subject who received a product.

   We assume that a NPG-subject’s pre-information is uncorrelated with the
    info treatment received by the PG-subject whom he or she talks to about
    the product.

   This excludes the following situation: If I know that a Sidekick has AOL
    messenger I will specifically seek out subjects who received a product and
    whom we told about the AOL messenger capability of the Sidekick.
   Effect of Info-Treated Friends on
   Knowledge (NPG)




Effect of PG-subject’s info-treatment on NPG-subject’s knowledge (only for subjects who
Reported to have talked to specific PG subject)
   Effect of Info-Treated Friends on
   Knowledge (NPG)
                                                            74.3
                         68.4




Effect of PG-subject’s info-treatment on NPG-subject’s knowledge (only for subjects who
Reported to have talked to specific PG subject and seen PG subject with product)
   Effect of Info-Treated Friends on
   Knowledge (NPG)
                                                            74.3
                         68.4




          Subjects who reported to have talked to a friend who had the product
          and whom they have seen use the product are 6% more likely
          to correctly answer a question about the feature if their friend had
          received an info treatment.




Effect of PG-subject’s info-treatment on NPG-subject’s knowledge (only for subjects who
Reported to have talked to specific PG subject and seen PG subject with product)
    IV-Regression – confidence in answer
                                                       FCONFIDENCE
                                   Talked       Talked about    Talked about     Talked
                                 about OR            OR seen        OR seen    about AND
                                     seen          (services)       (gadget)      seen
                                      (all)


FR_FCONFIDENCE                         .142**            .124          .151*        .184*
                                       (.054)          (.100)         (.064)       (.074)


Intercept                            61.617**       67.697**        59.495**     57.503**
                                      (5.626)       (10.124)         (6.795)      (7.790)


N                                      1,912             400           1,511       1,207




Significance Levels: #:10%   *: 5%     **: 1%
    IV-Regression – confidence in answer
                                                       FCONFIDENCE
                                   Talked       Talked about    Talked about     Talked
                                 about OR            OR seen        OR seen    about AND
                                     seen          (services)       (gadget)      seen
                                      (all)


FR_FCONFIDENCE                         .142**            .124          .151*        .184*
                                       (.054)          (.100)         (.064)       (.074)


Intercept                            61.617**       67.697**        59.495**     57.503**
                                      (5.626)       (10.124)         (6.795)      (7.790)


N                                      1,912             400           1,511       1,207




Significance Levels: #:10%   *: 5%     **: 1%
    IV-Regression - knowledge
                                                  FCORRECTANSWER
                                   Talked     Talked about    Talked about     Talked
                                 about OR          OR seen        OR seen    about AND
                                     seen        (services)       (gadget)      seen
                                      (all)


FR_FCORRECTANSWER                    .180**            .011         .246**       .325**
                                     (.067)          (.106)         (.077)        (.112)


Intercept                            .567**          .890**         .461**       .400**
                                     (.068)          (.107)         (.077)       (.109)


N                                    1,919             400           1,519       1,209




Significance Levels: #:10%   *: 5%   **: 1%
 IV-Regression - knowledge
                                                  FCORRECTANSWER
                                   Talked     Talked about    Talked about     Talked
                                 about OR          OR seen        OR seen    about AND
                                     seen        (services)       (gadget)      seen
                                      (all)


FR_FCORRECTANSWER                    .180**            .011         .246**       .325**
                                     (.067)          (.106)         (.077)        (.112)


Intercept                            .567**          .890**         .461**       .400**
                                     (.068)          (.107)         (.077)       (.109)
  Info-treatment of friend is used as instrument. Estimated social-learning
  effects are about 3-15 times greater than the average effects estimated across
N                                   1,919           400         1,519       1,209
  all subjects.



Significance Levels: #:10%   *: 5%   **: 1%
Observations
   Conditional on having communicated about the product social
    learning seems strongest for gadgets rather than services.

   This might indicate that visual observation is important for
    social learning.

   It is also possible that our feature set for gadgets provides a
    more natural decomposition of real-world communication than
    our feature set for services.
Summary
   Three methodological contributions
     Application–specific measure of social connectedness
     Hedonic analysis using configurators
     Measure of confidence using the Bobs

   Advertising increases information.
   Social learning is as important as effects of
    advertising.
   Future work:
     Disentangle weak and strong social learning channels
     Measure social influence.
Numbers
 2360 social network
 1200 baseline survey
 600 people eligible in each category
 100 people chosen
 1100 people follow-up survey
  Product Tester vs Eligible NonTester
                                         Eligible
Product
                                         Nontester
Tester



                                           F1
 F1




                                            F2
 F2




 F3                                         F3
Recipients               Recipients are asked to make predictions in 7 situations
                         (in random order): 1 direct friend; 1 indirect friend of
                         social distance 2; 1 indirect friend of social distance 3;
                         1 person from the same staircase; 1 person from the
                         same house; 2 pairs chosen among direct and indirect
                         friends
              Direct                          A possible pair
              Friend
                                                                         Share
                                                                        staircase
                                         Indirect       Indirect
    Direct                 Direct                        Friend
             Recipient                    Friend
    Friend                 Friend
                                          2 links        3 links



              Direct
              Friend                                                     Same
                                                                         house

				
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