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Responses to the Problem o= f Trust On-Line
Melanie C. Green
University of Pennsylvania
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sfMfx61lKm3JNvY1U0k0jRHSl+tGKMVZmHeiiigAopCM9SaUDHakMOlFFFMQUUUUgE5opTSDNAwA 9KKOaMUAJnml/CgjPekAP40ALiko59qDjFABijn0o+gpR9aAExSjNGPqaPegA69aTjpjil/CigBO O9FLik6GgAyfSl55o/nS0AJk0UUde9ABjPPSl6UUUAAOaMZ7UdaMCgD/2Q== ------=_NextPart_01C53DDE.D2F45870 Content-Location: file:///C:/D869C635/GreenCSItalk2005_files/slide0002.htm Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="us-ascii" Slide 1
Problem of Online Trust
¡Ease of deception
l
lVisual and nonverbal cues reduced or absent
lLack of mutual acquaintances
lLowered feelings of accountability
l
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Lower Generalized Trust Online
¡Do you think most people [on the Internet] are trustworth= y, or can’t you be too careful?
¡ <= /div>
lLower ratings for individuals “on the Internet”
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What do we mean by trust?
•Risk
•Emotional betrayal
•Privacy violations
•Physical harm
•
•
•Opportunity
•Emotional support
•Collective action
•Tangible support
l
l
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Specific versus General Trust
¡Specific trust:  confidence that a person will act in a particular way
¡
¡
= ¡General/global trust: confidence that a person acts in accordance with one’s best interests
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Intern= et Relationships:  Global Trust<= /span>
¡Emotional support
¡Honest
¡Keeping secrets
¡Physical safety
¡Lending money
¡Inviting to one’s home
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Trust-Relevant Information
<= span class=3DBB style=3D'position:absolute;left:-4.3%;top:.39em'>¡= Information provided by the person
¡
= ¡Information external to person (especially groups, social networks= )
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External information sources
¡Identity verification
¡
¡Reputation systems
¡
¡Social network systems
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Identity Verification
¡Mutual friends/acquaintances
¡
= ¡Third-party websites (e.g., employers)
¡
¡In-person meetings
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Survey Studies
¡Existing relationships that began on the Internet
¡
= ¡Similarity, disclosure, friendliness were much stronger predictors of trust among those who had verified identity
¡
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Basic Scenario (excerpt)
¡ Imagine that you regularly read an on-line = chatroom about a hobby of yours, and occasionally post messages to this chatroom.  = One of the other people on this chatroom (we= 217;ll call this perso= n X), responds to one of your messages with a personal email, and you begin an email exchange with X.  You’ve never met X in <= /span>person; you only know him/her through the <= /span>chatroom and email.  You have only been exchanging emails with X for a brief period of = time, about a week or so. During this period of= time, your email conversations with X have = evolved from discussions of your hobby to shari= ng slightly more personal details about your lives= , likes and dislikes, and so on…=
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Design
¡Length of relationship
¡ six months versus a few weeks
¡
¡Verification of identity
¡ mutual acquaintance versus not <= /div>
¡
¡Similarity
¡ high versus low
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Results: Verification X Similarity on Trust Composite
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Identity Verification Results
¡Main AND interactive effects in both survey and experiment
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Reputation
¡Proxy for word-of-mouth
¡
<= span class=3DBB style=3D'position:absolute;left:-4.76%;top:.39em'>¡Example: Ebay feedback ratings
¡
¡Positive or negative comments from interaction partners; summary rating linked to account name
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Research Question
¡Two compon= ents of the feedback system that should affect trust are the net rating and the % of negative feedbacks ¡What impact do sellers’ net rating and % of negative feedba= cks have on buyers’ bids and trust for the seller?
¡
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Sensitivity to Sample Size
¡= In in-person relationships, exemplars may <= /span>carry more weight than statistical/base-rate evidence
¡
¡F= eedback ratings may be better because they summarize the experiences of multiple interaction partners
¡
<= span style=3D'font-size:86%'>¡Do users take advantage of this feature?
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Method
¡Online stu= dy (N =3D 229; average age 28 years; 70% female)
¡
¡Between-Subjects Design:
¡2 (net feedback: high, medium, low)
¡X 2 (% negative: high, low)
¡
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Scenario
¡You log onto an auction site, looking for a used item, X, that usually sells for $85 new.  You’ve noticed that = items similar to X have been selling on the auctio= n site for $35-$50, plus shipping and handling of about $7-$8.  After looking for a bit, you find= an X that is exactly what y= ou want.  The auction ends in 2 = hours, and bid increments are $1.=
= ¡ Seller: sellerQ
¡ Net Feedback Rating: (a-b)*
= ¡ Positive Feedbacks: (a)*
¡ Negative Feedbacks: (b)*
= ¡ Current Price: $19
¡Item descriptio= n: “You are bidding on a used X.  It is in like-n= ew condition with all original components.&n= bsp; Winning bidder pays $7.50 s/h.”
= ¡
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Conditions
lLow net rating, Low % negative feedbacks
¡= Net Feedback Rating: 13
¡= ;Positive Feedbacks: 13, Negative Feedbacks: 0 (0%)=
lLow net rating, High % negative feedbacks
¡= Net Feedback Rating: 11
¡= ;Positive Feedbacks: 13, Negative Feedbacks: 2 (13.3%)
lMedium net rating, Low % negative feedbacks, =
¡= Net Feedback Rating: 51
¡= ;Positive Feedbacks: 52, Negative Feedbacks: 1 (1.9%)
lMedium net rating, High % negative feedbacks <= /span>
¡= Net Feedback Rating: 44
¡= ;Positive Feedbacks: 52, Negative Feedbacks: 8 (13.3%)
lHigh net rating, Low % negative feedbacks
¡= Net Feedback Rating: 509
¡= ;Positive Feedbacks: 518, Negative Feedbacks: 9 (1.7%)
lHigh net rating, High % negative feedbacks
¡= Net Feedback Rating: 439
¡= ;Positive Feedbacks: 518, Negative Feedbacks: 79 (13.2%)
¡
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Dependent Variable examples
¡How likely woul= d you be to bid on sellerQ’s X before the close of the auction?
 = ¡What is the maximum bid you would be willing to place on sellerQ’s X?
    ¡How much do you trust sellerQ to follow through on the transaction?
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Bidding and Trust by % Negative
3.29
4.08
Trust that seller will refund m= oney
4.26
5.07
Trust that seller will send ite= m in good condition
4.21
5.10
Trust that seller will send ite= m on time
4.49
5.38
Trust that seller will follow t= hrough on transaction
4.23
4.59
Maximum bid for seller’s item
4.69
5.53
Likeliness to bid on seller’s item
High % of
Negative Feedbacks
Low % of=
Negative Feedbacks
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Bidding and Trust by Net Rating
3.25
4.48
4.48
4.80
4.54
4.99
High
Net Rating
4.56
4.79
Trust that seller will send ite= m on time
4.51
4.87
Trust that seller will send ite= m in good condition
3.58
3.91
Trust that seller will refund m= oney
4.81
5.08
Trust that seller will follow t= hrough on transaction
4.18
4.50
Maximum bid for seller’s item
4.94
5.29
Likeliness to bid on seller’s item
= Medium Net
Low
Net Rating
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Interaction Effects?
¡No interac= tion between percent negative and net feedback ratings on trust or bidding
¡
¡Insensitivity to sample size
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Social Network Systems
¡Draw on existing social groups or networks
¡
= ¡Blurring boundaries between online and offline
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Friendster
¡Links peop= le with friends and friends of friends (“second degree friends”, “third degree friends”)
¡
¡“Fun and safe”
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Facebook (www.thefacebook.com)
¡Students can create and view profiles of other people at their own college/university
¡
¡Can provide photos, relationship information, hobbies, etc.
¡
¡Other users c= an leave comments, be listed as a “friend”
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Example Facebook Groups
¡Hamilton House Staff
¡Penn Punk Rock
<= span class=3DBB style=3D'position:absolute;left:-4.97%;top:.39em'>¡Aileen is unbelievably Amazing
¡Anime Club
¡Body Piercings: We like Metal
¡Connecticut Pride
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Facebook and Friendster study
¡Have you used the site?
¡
¡How frequently?
¡
¡Met new people on the site?
¡
¡Trust people met on the site?
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Facebook
¡Most had used the site
¡
= ¡Some had met new people, most used it for gaining additional information about people encountered in passing
¡
¡
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Trust in People Met on Facebook
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Frequency of use, percept= ions of honesty, and disclosure
¡Positive correlations between frequency of using Facebook, belief= that people are honest in the information they post on Facebook, = and the amount of personal info disclosed on Facebook
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Friendster
¡Infrequent= ly used among this sample
¡
¡Not a boost to trust
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Concluding thoughts on Trust
¡Optimal level of trust?
¡
= ¡Trust and additional relationship dimensions
¡
<= span class=3DBB style=3D'position:absolute;left:-4.73%;top:.39em'>¡Trust and romantic relationships
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