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The role of interpersonal information in electronic commerce: The case of Internet auctions Avi Noy The Graduate School of Business Administration University of Haifa http://research.haifa.ac.il/~avinoy/ [email protected] Contents.

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The role of interpersonal information in electronic commerce:The case of Internet auctions Avi NoyThe Graduate School of Business AdministrationUniversity of Haifahttp://research.haifa.ac.il/~avinoy/ [email protected]

slide2

Contents

  • Information and interaction in electronic commerce
  • Internet auctions
  • A study of interpersonal information in auctions (Supervised by Prof. Sheizaf Rafaeli)
slide3

Information and interaction in electronic commerce

Our focus is this study id on the consumer in B2C and C2C

  • What type of information is consumed
    • Product related, Seller related (and 3rd party sites), …
  • Sources of information
    • Public / Interpersonal information (real vs. virtual), Advertisements, Other sites,…
  • Direction of the information
    • One way / Two ways
  • Type of communication
    • Textual, Graphical, audio, video, synchronous/Asynchronous
current research

Related topics

  • Human Computer Interaction
  • Autonomous agents
Current research

Interpersonal

Influence

Computer-

Mediated

Communication

Consumer

Behavior

How are these

issues related ?

Virtual

Presence

Internet

Auctions

slide5

Characters (VHost) – OddCast

Human click’s interactive salesman

BuddySpace

Information and interaction in electronic commerce

  • How to represent an interaction?
slide6

Information and interaction in electronic commerce

  • OddCast
    • Banners that said, “Chat online with an expert” with a gif of a smiling service vs. [V]Host™ character saying, “Hi, I’m a customer service agent. Click here for live help.”

Generated 150% improvement in click through rate to chat

    • Users create [V]Hosts and email them to friends as part of a contest for the awards night.

62% of unique visitors converted into registrants

    • Promoting website as alternative to traditional mailing to lower customer service costs and postal fees.

With no advertising or change in their search engine status, Merit put a [V]Host™ on their website. Sustained lift of 200% in traffic

slide7

Bubble - IBM

Radar- Odigo

Interaction map

Information and interaction in electronic commerce

  • How to represent an interaction and awareness?
slide8

Chat Circles – MIT Media Lab

Crowd – MIT Media Lab

FootPrint – MIT Media Lab

Information and interaction in electronic commerce

  • How to represent an interaction and awareness?
slide9

Information and interaction in electronic commerce

  • Interpersonal information ? – Store rating, opinions
slide10

Information and interaction in electronic commerce

  • Interpersonal information in Internet auctions
    • Forums / Chats
    • Seller/Buyer reputation systems
slide11

Determinants of bidding behavior in Internet Auctions

The Bidder

perceived risk, independent estimates,

experience, information , enjoyment

  • Where to buy
  • What item
  • Bidding strategy
    • Bidding proxy
    • How much to bid
    • When to bid
    • How many bids

Auction mechanism and rules

auction type, ending rules, reserved price,

proxy bidding

The Item

Independent private value/Common value

Means of item evaluation

Bidding

behavior

The Seller

Reputation (self/site)

Other bidders and other social factors

herding, Precedingbehavior

slide12

Social influence in Internet auctions

Pre-Auction Phase

Bidding Phase

Post-Auction Phase

Auction related factors

(Auction type and rules)

Evaluation

Of auction

results

  • Information
  • Item
  • Auction site
  • Seller

Bidder related factors

(Risk, Experience, Enjoyment)

Changing factors

(Item evaluation, Recent information)

On Going

Decisions

Post-Auction

Decisions

Preliminary

Decisions

Seller related factors

(Reputation)

Social Influence

Virtual, Real

Social Influence

Virtual, Real

Other bidders related factors

(Preceding behavior, Evaluation )

Other social factors

(Friends, Family)

slide13

Theoretical background of the study

  • Normative vs. Informational influence
    • According to normative influence, judgment shifts result from exposure to others’ choice preferences and subsequent conformity to the implicit or explicit norms in these preferences.
    • Informational influence attributes shifts to the incorporation of relevant arguments or information about the issue that are shared between discussants (Kaplan, 1987)
  • Related theories
    • Influence in CMC groups
    • Social presence theory
    • Media Richness theory
    • Auction economics research
slide14

Research questions

  • Can the social environment that is part of traditional auctions be replicated in Internet auctions, and how?
  • How does other bidder influence bidding behavior?
  • What are the influencing components of interpersonal interaction in auctions?
  • How does bidding behavior affected by different auction models?
slide15

Research framework

  • Core simulation
    • Auction site
    • Interpersonal information components
    • Bidding agents
    • Implemented in Java
    • Input parameters - control setup and behavior
    • Output parameters – data collected during the auction
  • Simulation framework
    • Client - Web pages, Forms, Java scripts
    • Server - Perl/CGI scripts
  • Experimental procedure
    • Different auction models
    • Manipulation of the level of interpersonal information
slide19

Results – English auction

580

6

560

Number of bids

Of a winner

Win Bid

Number of bids

5

540

4

520

Bids

3

500

Number of bids

High Bid

2

480

1

460

0

440

HI Participants

HI Participants

LI Participants

LI Participants

slide20

Results – English auction

100%

% Continue

90%

80%

70%

% Wins

60%

50%

40%

30%

20%

HI Participants

LI Participants

slide21

Results – Dutch auction

100%

% Continue

620

90%

600

% Wins

80%

580

70%

Win Bid

560

Bids

60%

540

50%

520

40%

500

30%

480

20%

HI Participants

HI Participants

LI Participants

LI Participants

slide22

Future research and availability

  • Interpersonal information in e-commerce
    • Online Stores
    • Online games
    • Online casinos
  • Web mining – recommendations based bidding patterns
  • Autonomous agents
  • A demo version of the simulations is available at:

http://research.haifa.ac.il/~avinoy/auction/

Thank You !

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