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Markets as Conversations Making the Invisible Hand Visible

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.

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Markets as Conversations Making the Invisible Hand Visible

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  1. Markets as ConversationsMaking the Invisible Hand Visible Robert Lusch Daniel Zeng Hope Jensen Schau

  2. Markets As …

  3. 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.

  4. 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.

  5. Critical Events • Exogenous Events: outside the system • Multiple Stressors: high-impact • Domain: Regional, National, Global • Influence a Market System

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. Alexa Web Traffic Ranking: Dec. 2005 vs. March 2010

  11. World-wide Share of Online Time • 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. 11

  12. 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

  13. Share Links

  14. Delicious Social Networks

  15. 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)

  16. 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

  17. H1N1

  18. Michael Jackson’s Death

  19. Windows 7 Launch

  20. 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

  21. Findings

  22. Findings • All these curves follow cyclic trends with different periodicities • More cycles indicate richness of the events • Michael Jackson’s death involved several sub-topics 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

  23. Case Study II: Community Question and Answer (CQA) • Another widely-adopted Web 2.0 technology

  24. Yahoo! Answer Statistics

  25. 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?

  26. 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

  27. # of Questions over Time June 9th is the Apple Worldwide Developer Conference: 3G iPhone is announced June 17th: iPhone software upgrade

  28. Google Trend Data for the Same Time Period

  29. 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

  30. Example Communities • User u3 contributed to the community through answering while u5 never answered questions from other users. Other users performed both activities.

  31. Identifying Overlapping Communities • After training with LDA, the weighed user adjacent matrix is split into the asker-community matrix and answerer-community matrix • Elements of the asker-community matrix indicating the probability distribution over askeri given community k • Elements of the answer-community matrix indicating the probability distribution over answerer j given community k.

  32. 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

  33. Community Evolutionary Pattern Identified by LDA

  34. 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.

  35. 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.

  36. 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.

  37. 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

  38. 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

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