Reputation systems
Sunday, May 25th, 2008I’ve been developing a model where companies can be, not like plantations with owners and bosses, but like towns.
Company as town. Right now we usually sell shares of a company, and people who own shares decide what the people who work at the company will do. But picture a company as a town. Who owns New York City? I live in New York City. I work in New York City. I can own real estate, which is similar to Class B stock without voting rights, or to local currency.
Virtual land as stock without voting rights. Buying and selling blocks of land is fine, and recently instead of giving a stakeholder 1/5th of profits for work he’d done to help my business get started, I gave him one block out of five in a virtual town, but we can make the experience of owning land even more attractive.
Ratings. Every service and person can set up shop on the virtual land, like building real estate on land. Picture the squares of a checkerboard. I start my retail makeover service on a square. Customers rate my services a 9 out of 10, in answer to the question, “How likely are you to recommend this service to a friend?” I start my narrative learning theory class on another square. Customers rate that class a 7 out of 10. As other people who work in the “town” offer services, each service gets a reputation.
Counter-intuitive. Think of a time when you’ve had a great experience with a salesperson or someone in customer service. Now, because of your great experience with that sales representative, are you much more likely, a little more likely, or not at all more likely to want to talk to someone they work with? What about their company as a whole? Because of your great experience with this person, are you much more likely, a little more likely, or not at all more likely to want to do business with the company again? With me, because I had a great experience with a salesperson buying my laptop at a Best Buy store in Atlanta, I’m only a little more likely to want to interact with another salesperson at that store, but I’m much more likely to want to buy again from Best Buy.
The Atlanta theory of influence. There’s a restaurant in Atlanta that I absolutely love. I rate the restaurant a 10 out of 10. The block the restaurant is on though, is only made a little bit better by the restaurant. I’m only a little bit more likely to go to another business on that block. And the restaurant has no impact on how much I like the neighborhood, which is run-down. The restaurant has a huge impact on how much I like Atlanta. As soon as I ate at the restaurant, I became much more likely to want to go to Atlanta.
Modeling. So in this virtual town, which is a new kind of company, I’m setting up a reputation system where relationships and influence are modeled visually. When someone rates my retail makeover service a 9 out of 10, that has a small positive influence on the services which are located nearby to mine. It has no influence on the neighborhood — the bigger area of checkerboard squares. And it has a big positive influence on the town — the whole checkerboard.
Benefits. Let’s say there are 1,000 people working at a company-as-town. Each person has a rating. Each service has a rating. Each workgroup or block has a rating. Each department or neighborhood has a rating. The company as town has a rating. Ratings are useful. People and services with the highest ratings will benefit from high ratings points as do businesses rated on Citysearch.com or Yelp.com — you see a service is good by its reputation. If a company takes a small portion of income to each service or person, just like cities collect taxes on income, then the company can even redistribute income based on points. A big benefit to grouping relationships — people who work together — in this locality way, is that people on the same block can pool their resources to organize a block party, and people in the same neighborhood can pool their resources to create a website which attracts customers.
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September 23rd, 2008 at 4:34 pm
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