Organizational Sociology & Googles Enterprise Prediction Markets

Graduate student Ben Spigel&#8217-s comment on Richard Florida&#8217-s blog:

About a decade ago, a group of cognitive scientists looking at Bell Labs found that all things being equal, the chances of two scientists collaborating was 4 times higher if they had offices in the same hallway, than if there was a turn in the hall between them. Basically, people are lazy about talking to other people. There&#8217-s a noticeable drop in communication when you have to turn your neck to see someone.


Robin Hanson in a comment on Marginal Revolution:

This is important work for organizational sociology, but not for prediction markets, as this does little to help us find and field high value markets.


Robin Hanson:

Info Value = the added accuracy the markets provide relative to other mechanisms, times the value that accuracy can give in improved decisions, minus the cost of maintaining the markets, relative to the cost of other mechanisms.

A highly accurate market has little value if other mechanisms can provide similar accuracy at a lower cost, or if few substantial decisions are influenced by accurate forecasts on its topic.

Related Links:

Using Prediction Markets to Track Information Flows: Evidence From Google – (PDF file – PDF file) – by Bo Cowgill (Google economic analyst), Justin Wolfers (University of Pennsylvania) and Eric Zitzewitz (Dartmouth College)

Author Profile&nbsp-Editor and Publisher of Midas Oracle .ORG .NET .COM &#8212- Chris Masse&#8217-s mugshot &#8212- Contact Chris Masse &#8212- Chris Masse&#8217-s LinkedIn profile &#8212- Chris Masse&#8217-s FaceBook profile &#8212- Chris Masse&#8217-s Google profile &#8212- Sophia-Antipolis, France, E.U. Read more from this author&#8230-

Read the previous blog posts by Chris. F. Masse:

  • Are David Pennock’s search engine prediction markets the worst marketing disaster since the New Coke?
  • Midas Oracle is incontestably [*] the best vertical portal to prediction markets.
  • Comment spam paid by Emile Servan-Schreiber of NewsFutures-Bet2Give
  • BetFair Games needs a Swedish provider to develop its gambling offerings.
  • When Markets Beat the Polls – Scientific American Magazine
  • Robin Hanson has some fanboy in India. Great. Tiny caveat: The parroting Indian writer does not acknowledge Robin Hanson by name.
  • Molecular Nanotechnology

3 thoughts on “Organizational Sociology & Googles Enterprise Prediction Markets

  1. Michael Giberson said:

    The more I think about Hanson’s remark, the less I believe it.

    He writes as if the value of an enterprise prediction market is something independent of the nature of the enterprise within which it may be situated.

    Sure, in the abstract, a prediction market is a prediction market is a prediction market. In practice, individual organizations either adopt prediction markets or not, and find them useful or not, and whether or not the organization finds prediction markets useful may depend on many things other than the obvious natural beauty of the LMSR.

    If prediction market scholarship is going to be helpful in answering the question of when and where a prediction market will work, research in the “organizational sociology” of prediction markets will need to be done.

  2. Mat Fogarty said:

    Giberson has hit the nail on the head. The key issue in adoption of prediction markets is about the organizational issues, not about the design of the actual transactional instruments (LMSR etc), or the cost benefit of improved accuracy. Corporations are not that logical.

    Most companies rely on a hierarchical system of management. A prediction market, used widely in the organization, has little respect for a hierarchy. All participants receive the same starting balance, it operates as a meritocracy, and information is shared.

    Consistent biases exist in corporate forecasting – over optimistic ship dates, lowballed sales forecasts, sandbagged spending forecasts etc. These biases persist because they give power to the controller of the forecast. This is no longer the case with prediction markets. If a ship date is wrong, the market will correct it, if a sales forecast is off, the market will correct it. This unfettered honesty reduces power of middle management; the power now being given back to the company as a whole. Given this, as observed at Microsoft, “prediction markets are popular at the extremes of the organization” – but it is middle management who cuts the PO and has the power to undermine use of a market.

    The Google paper is important for prediction markets. Markets need to fit into the corporation, and markets have a huge effect on information flows. Understanding the basics of information flows in a corporation is a key first step to understanding how prediction markets can be more widely adopted.

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