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Small is beautiful,but it is also efficient——小不仅美，而且高效 已有3人参与
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商业和政治领域的专家都在谈论规模经济。他们说项目和机构规模的增加能够节约成本。不过当这些项目和机构太大时，产生的收效就不是那么有高效了。虽然规模能产生明显的好处，但也隐藏着风险——它增加了发生巨大损失的可能性。100 000 000 美元的项目虽然看起来合理，但是相比于10 000 000 美元的项目，同一件事它也会花费更多的时间和金钱。当规模达到一定的临界点时，就会变得非常脆弱，而且也会吞噬规模增加带来的好处。想知道大的事物会多么的脆弱，可以考虑大象和老鼠之间的差异：前者会因为最轻微的跌倒而摔断大腿，而后者即使从几倍于其身高的地方掉下来仍然毫发无损。这解释了为什么老鼠的数量远远超过大象。 所以我们需要将决定和项目分散为尽可能多的单元，通过把失误分散到更广范围，增强系统。事实上，我曾论证过政府（决策的）分散有利于降低公共赤字。很大一部分赤字来源于低估了项目花费，这种低估在那些大的、至上而下的政府中更加严重。瑞士的以州为基础、自下而上的体系是成功的。与此形成对比的是，苏联、伊拉克和叙利亚集权主义的失败。 网上看的一篇文章的片段，很喜欢，所以把它翻译下来了；无责任，非专业翻译。 原文： Experts in business and government are always talking about economies of scale. They say that increasing the size of projects and institutions brings costs savings. But the "efficient," when too large, isn't so efficient. Size produces visible benefits but also hidden risks; it increases exposure to the probability of large losses. Projects of $100 million seem rational, but they tend to have much higher percentage overruns than projects of, say, $10 million. Great size in itself, when it exceeds a certain threshold, produces fragility and can eradicate all the gains from economies of scale. To see how large things can be fragile, consider the difference between an elephant and a mouse: The former breaks a leg at the slightest fall, while the latter is unharmed by a drop several multiples of its height. This explains why we have so many mice than elephants. So we need to distribute decisions and projects across as many units as possible, which reinforces the system by spreading erros across a wider range of sources. In fact, I have argued that government decentralization would help to lower public deficits. A large part of these deficits comes from underestimating the costs of projects, and such underestimates are more severe in large, top-down governments. Compare the success of the bottom-up mechanism of canton-based decision making in Switzerland to the failure of authoritarian regimes in Soviet Russia and Baathist Iraq an Syria ——Nassim Nicholas Taleb Learning to Love Volatility from WSJ |
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2楼2012-12-07 15:57:00
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3楼2012-12-14 00:57:20
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