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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]


Contents commerce:

  • Information and interaction in electronic commerce

  • Internet auctions

  • A study of interpersonal information in auctions (Supervised by Prof. Sheizaf Rafaeli)


Information and interaction in electronic commerce 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

Current research

Interpersonal

Influence

Computer-

Mediated

Communication

Consumer

Behavior

How are these

issues related ?

Virtual

Presence

Internet

Auctions


Characters (VHost) – OddCast commerce:

Human click’s interactive salesman

BuddySpace

Information and interaction in electronic commerce

  • How to represent an interaction?


Information and interaction in electronic commerce 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


Bubble - IBM commerce:

Radar- Odigo

Interaction map

Information and interaction in electronic commerce

  • How to represent an interaction and awareness?


Chat Circles – MIT Media Lab commerce:

Crowd – MIT Media Lab

FootPrint – MIT Media Lab

Information and interaction in electronic commerce

  • How to represent an interaction and awareness?


Information and interaction in electronic commerce commerce:

  • Interpersonal information ? – Store rating, opinions


Information and interaction in electronic commerce commerce:

  • Interpersonal information in Internet auctions

    • Forums / Chats

    • Seller/Buyer reputation systems


Determinants of bidding behavior in Internet Auctions commerce:

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


Social influence in Internet auctions commerce:

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)


Theoretical background of the study commerce:

  • 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


Research questions commerce:

  • 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?


Research framework commerce:

  • 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



English Auction commerce:


Dutch Auction commerce:


Results – English auction commerce:

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


Results – English auction commerce:

100%

% Continue

90%

80%

70%

% Wins

60%

50%

40%

30%

20%

HI Participants

LI Participants


Results – Dutch auction commerce:

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


Future research and availability commerce:

  • 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/

  • Simulations can be operated in class or at home

  • Contact: [email protected]

    Thank You !


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