Transcript How Critical Events Trigger Social Production: The

Markets as Conversations
Making the Invisible Hand Visible
Robert Lusch
Daniel Zeng
Hope Jensen Schau
Markets As …
Main Thesis
“Invisible hand” assumes a machine-like economy
where unseen co-ordination seeks an equilibrium for
supply and demand.
Web 2.0 technology (e.g., social bookmarking, social
networks, blogs) makes market actors’ coordination
efforts manifest in certain contexts.
Our research reveals examples of technologically
mapping market conversations at particular critical
moments in time, and glimpsing the no longer
invisible hand.
All Actors are Resource Integrators
Service-Dominant Logic’s (Vargo and Lusch
2004, 2008) foundational premise #9 states
"All social and economic actors are resource
integrators” meaning that market actors
gather together resources from disparate
sources to satisfy needs.
So, with a critical event we would
expect to see even more resource
integration.
Critical Events
Exogenous Events: outside the system
Multiple Stressors: high-impact
Domain: Regional, National, Global
Influence a Market System
Theoretical Foundation
Chaos theory suggests how certain
conditions can change and
permanently alter a system. Like the
butterfly effect, critical events change
the course of a system because of the
initial conditions that underlie the
system.
Piotrowski 2006: Hurricane Katrina and
the implications of chaos theory
Alesch 2004: Theory of Disaster
Recovery
This would suggest that each change is
independent initially but that it disrupts the system.
Theoretical Foundation
Prior literature on macroeconomics
reveals that critical events drive short
term and even lasting impacts on
people’s interests and discourse
surrounding a domain (social
production).
Hall 2005: adverse macroeconomic
effects of oil price increases
Zivot and Andrews 2002: examine short
and long term impacts of Great Crash of
1929 and the of Oil Price Shock of 1973
This suggests that that a critical
economic event impacts exchange
systems in the short run and changes
market discourse in the long run.
Assumption 1
Web 2.0 platforms such as
social bookmarking and
community question and
answer can illuminate the
trajectory of market
discourse.
Web 2.0 provides multiple
modes of market discourse,
which captures the
integration of resources by
market actors.
Assumption 2
Mapping the impact of critical events through
social bookmarking and community question
and answer is a Natural Experiment
Instrument
Tags used/posted by and the questions/answers
from the users provide an unbiased
representation of their information-seeking needs
and their resource integration efforts.
This means that we can trace the impact of a
critical event on resource integration through
market discourse observed on Web 2.0 platforms.
Alexa Web Traffic Ranking: Dec.
2005 vs. March 2010
World-wide Share of Online Time
14% 6%
Category didn’t exist
three years ago
35%
8%
22%
16%
All Other
Communications
Social Connections
Shopping & Travel
Entertainment & Leisure
Work, Business & Education
• In August 2009, 17 percent of all time spent on the Internet was at social networking sites, up from 6
percent in August 2008.
• Estimated online advertising spending on the top social network and blogging sites increased 119
percent, from approximately $49 million in August 2008 to approximately $108 million in August 2009.
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Case Study I: Social Bookmarking
• A widely-adopted Web 2.0 technology
“Delicious is a social bookmarking website, which
means it is designed to allow you to store and share
bookmarks on the web, instead of inside your
browser.” － delicious.com
Share Links
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Delicious Social Networks
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Delicious Dataset Used
Tagging history of 43.5K users covering the period
1/1/2009 --- 11/5/2009, with 3.2M URLs, 0.6M tags, and
17M tagging activities
Key data elements
Tags used; Web pages/URLs tagged; timing of tagging; user id
Events studied:
H1N1 outbreak (April 2009)
Michael Jackson’s death (June 25, 2009)
Windows 7 launch (October 22, 2009)
Analysis I: Weekly Measures
Studied
– Intensity: # of tagging activities
– Reach: # of users involved
– Depth: # of related URLs
– Impact:
• Indicators for peaks in measurement
• Repercussions after peaks
H1N1
Michael Jackson’s Death
Windows 7 Launch
Analysis II: 2-day Measures
– Burstiness：% change in interest / time needed
to go from ½ (peak+average) to peak
– Half-life：time needed to go from peak to ½
(peak+average)
– Width：time between two adjacent ½
(peak+average) points
– Persistency：time in which interest in an event
is higher than the average level
– Lag：time between occurrence of an event and
responses on the tagging site
Findings
Event
Burstiness
(%/hour)
7.2
Width
(day)
Half-life
（day）
Persistency Lag (day)
(day)
6
3
14
~15
Michael
Jackson
0.7
14
3
20
1~2
Windows
7
2.9
8
3
180
-180
H1N1
Findings
• All these curves follow cyclic trends with
different periodicities
• More cycles indicate richness of the events
– Michael Jackson’s death involved several subtopics and resulted in ups-and-downs in interest
• For unexpected events such as H1N1 and
Michael Jackson’s death, show clear spikes
immediately
• For predictable events such as the Windows 7
launch, the spikes occur in cycles before event
and spike with event
Case Study II: Community Question
and Answer (CQA)
• Another widely-adopted Web 2.0 technology
Yahoo! Answer Statistics
Research Agenda
• For critical incident and market disruptions,
how can we capture the coordination and
market conversation?
– How does a user community’s interest of a
product (community topic) change over time?
– How do the community topics serve as an eWOM
branding mechanism?
Dataset Used
• All the resolved questions about iPhone (a market
disruption) and their associated answers during the
period of May 26, 2009 to Aug. 20, 2009, from
Yahoo! Answers, with more than 16,000 question
threads.
• From each question thread, we extracted the
following fields
– asker, question context, question timestamp, and
associated answers
– each associated answer covering answer content,
answerer who posted the answer, and timestamp
# of Questions over Time
600
Jun. 17th
500
number of questions
Jun. 9th
400
300
200
100
0
May 26th
0
10
20
30
40
50
time offset (days)
60
70
June 9th is the Apple Worldwide Developer Conference: 3G iPhone is announced
June 17th: iPhone software upgrade
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Google Trend Data for the Same
Time Period
Constructing CQA Interactive
Network
• Each unique user id in the dataset as a vertex
• An edge <i,j> indicating that a question posed
by user i was answered by userj
• Each edge <i,j> in the network weighted by
the number of i ’s questions that were
answered by j
Example Communities
• User u3 contributed to the community through
answering while u5 never answered questions from
other users. Other users performed both activities.
Identifying Overlapping
Communities
• After training with LDA, the weighed user
adjacent matrix is split into the askercommunity matrix and answerer-community
matrix
– Elements of the asker-community matrix
indicating the probability distribution over asker i
given community k
– Elements of the answer-community matrix
indicating the probability distribution over
answerer j given community k.
Identified Threads
•
•
•
•
•
•
Thread a: syncing w/ iTunes
Thread b: contract and pricing
Thread c: releasing of new iPhone OS
Thread d: comparison w/ other smart phones
Thread e: data plan and jailbreak
Thread f: signing and upgrading service
contract
• Thread g: signing contract for iPhone 3GS
• Thread h: basic usage
Community Evolutionary Pattern
Identified by LDA
5 Stages of iPhone Discussions
• Value-in-Exchange Discussions May 26th—Jun.
11th: Discussions focused on signing contract
and the price of upgrading iPhone. Keywords
such as “contract”, “price”, “upgrade”, “data”,
“plan” ranked highly in most communities.
• Use Discussions Jun. 12th—Jun. 28th: Discussions
focused on transferring video and music from
computer to iPhone and the scheduled release
of iPhone OS 3.0. Keywords such as “release”,
“June”, “check”, “iTunes”, “video”, “transfer”,
ranked highly in communities.
5 Stages (Cont’d)
• Competitive Value Propositions Jun. 29th—Jul.
15th: Discussions focused on comparing the
newly released iPhone with other smart
phones, particularly with Palm Pre. The AT&T
mobile network was also often compared with
those from other service providers such as
Verizon, and received many complaints.
Keywords such as “network”, “verizon”,
“palm”, ranked highly.
5 Stages (Cont’d)
• Specific Device Attributes Discussions Jul. 16th—
Aug. 01th: Discussions focused more on usage and
performance. Keywords such as “touch”,
“keyboard”, “battery”, “network” ranked highly.
• Resource Integration Discussions Aug. 02th—Aug
20th: Discussions focused on more advanced
usage of iPhone, e.g., converting videos or music
in any format to iPhone. Also many users started
to exchange free softwares for jailbreak iPhone.
Keywords such as “convert”, “jailbreak”, “unlock”
ranked highly.
Summary
Observable market discourse allows us to
empirically study the coordination efforts
involved in the “invisible” market-making process
Markets as Conversations
Mapping market discourse through examining
social bookmarking and CQA is a form of Natural
Experimentation.
Initial empirical findings suggest rich and
meaningful patterns can be automatically mined
from a range of Web 2.0 platforms
Ongoing Research
Extensive econometric testing
Non-trivial linkage to existing theory and
possible development of new theory
Identifying and classifying different types
and patterns of impact of events
Case studies in marketing with specific
managerial implications