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From the lead author of the international bestseller Limits to Growth

Thinking in Systems
A Primer

Thinking in Systems 系统思考

Other Books by Donella H. Meadows:
Donella H. Meadows 的其他书籍:

Harvesting One Hundredfold: Key Concepts and Case Studies in Environmental Education (1989). The Global Citizen (1991). with Dennis Meadows: Toward Global Equilibrium (1973).
收获百倍:环境教育的关键概念和案例研究》(1989 年)。全球公民》(1991 年),与 Dennis Meadows 合著:Toward Global Equilibrium》(1973 年)。
with Dennis Meadows and Jørgen Randers:
Beyond the Limits (1992).
超越极限》(1992 年)。
Limits to Growth: The 30-Year Update (2004).
增长的极限》:30 年更新》(2004 年)。
with Dennis Meadows, Jørgen Randers, and William W. Behrens III: The Limits to Growth (1972).
与 Dennis Meadows、Jørgen Randers 和 William W. Behrens III 合著:《增长的极限》(1972 年)。

with Dennis Meadows, et al.:
与 Dennis Meadows 等人合作:

The Dynamics of Growth in a Finite World (1974).
有限世界中的增长动力》(1974 年)。
Groping in the Dark: The First Decade of Global Modeling (1982).
在黑暗中摸索:全球建模的第一个十年》(1982 年)。
WITH J. Robinson: WITH J. Robinson:
The Electronic Oracle: Computer Models and Social Decisions (1985).
The Electronic Oracle:计算机模型与社会决策》(1985 年)。

Thinking in Systems 系统思考

  • A Primer — 初级读本

Donella H. Meadows

Edited by Diana Wright,
Sustainability Institute
publishing for a sustainable future
伦敦 弗吉尼亚州斯特林
First published by Earthscan in the UK in 2009
Earthscan 于 2009 年在英国首次出版
Copyright by Sustainability Institute.

All rights reserved 保留所有权利

ISBN: 978-1-84407-726-7 (pb)
ISBN: 978-1-84407-725-0 (hb)
Typeset by Peter Holm, Sterling Hill Productions
Cover design by Dan Bramall
封面设计:Dan Bramall
For a full list of publications please contact:
Dunstan House 邓斯坦之家
14a St Cross St
London, EC1N 8XA, UK
英国伦敦 EC1N 8XA
Tel:  电话
Fax:  传真
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22883 Quicksilver Drive, Sterling, VA 20166-2012, USA
Earthscan publishes in association with the International Institute for Environment and Development
Earthscan 与国际环境与发展研究所联合出版
A catalogue record for this book is available from the British Library
Library of Congress Cataloging-in-Publication Data has been applied for.
At Earthscan we strive to minimize our environmental impacts and carbon footprint through reducing waste, recycling and offsetting our emissions, including those created through publication of this book. For more details of our environmental policy, see www.earthscan.co.uk.
在 Earthscan,我们通过减少废物、循环利用和抵消 排放物(包括出版本书所产生的排放物),努力将我们对环境的影响和碳足迹降至最低。有关我们环境政策的更多详情,请参阅 www.earthscan.co.uk。
This book was printed in the UK by TJ International Ltd, an ISO 14001 accredited company. The paper used is FSC certified.
本书由获得 ISO 14001 认证的 TJ 国际有限公司在英国印刷。所使用的纸张通过了 FSC 认证。
Part of this work has been adapted from an article originally published under the title "Whole Earth Models and Systems" in Coevolution Quarterly (Summer 1982). An early version of Chapter 6 appeared as "Places to Intervene in a System" in Whole Earth Review (Winter 1997) and later as an expanded paper published by the Sustainability Institute. Chapter 7, "Living in a World of Systems," was originally published as "Dancing with Systems" in Whole Earth Review (Winter 2001).
本文部分内容改编自最初发表在《共同进化季刊》(1982 年夏)上的一篇文章,标题为 "全地球模型与系统"。第 6 章的早期版本以 "介入系统的地点 "为题发表在《整个地球评论》(1997 年冬)上,后来作为扩展论文由可持续发展研究所出版。第 7 章 "生活在系统的世界中 "最初以 "与系统共舞 "为题发表于《整个地球评论》(2001 年冬)。
and for all those who would learn from her


A Note from the Author | ix
作者说明 | ix
A Note from the Editor xi
编者的话 xi
Introduction: The Systems Lens

Part One: System Structures and Behavior

ONE. The Basics
TWO. A Brief Visit to the Systems Zoo | 35
TWO.对系统动物园的简短访问 | 35

Part Two: Systems and Us

THREE. Why Systems Work So Well
FOUR. Why Systems Surprise Us 86
4.为什么系统会给我们带来惊喜 86
FIVE. System Traps . . and Opportunities | 111
系统陷阱.系统陷阱......与机遇 | 111

Part Three: Creating Change-in Systems and in Our Philosophy

SIX. Leverage Points-Places to Intervene in a System | 145
六.杠杆点--干预系统的位置 | 145
SEVEN. Living in a World of Systems | 166
七.生活在系统世界中 | 166

Appendix 附录

System Definitions: A Glossary | 187
系统定义:词汇表 | 187
Summary of Systems Principles | 188
Springing the System Traps | 191
跳出系统陷阱 | 191
Places to Intervene in a System | 194
干预系统的位置 | 194
Guidelines for Living in a World of Systems | 194
生活在系统世界中的指南 | 194
Model Equations | 195
模型方程 | 195
Notes | 204 注释
Bibliography of Systems Resources | 208
系统资源参考书目 | 208
Editor's Acknowledgments | 211
编辑致谢 | 211
About the Author
Index  索引


This book has been distilled out of the wisdom of thirty years of systems modeling and teaching carried out by dozens of creative people, most of them originally based at or influenced by the MIT System Dynamics group. Foremost among them is Jay Forrester, the founder of the group. My particular teachers (and students who have become my teachers) have been, in addition to Jay: Ed Roberts, Jack Pugh, Dennis Meadows, Hartmut Bossel, Barry Richmond, Peter Senge, John Sterman, and Peter Allen, but I have drawn here from the language, ideas, examples, quotes, books, and lore of a large intellectual community. I express my admiration and gratitude to all its members.
本书是数十位富有创造力的人士三十年系统建模和教学智慧的结晶,他们中的大多数人最初都在麻省理工学院系统动力学小组工作,或受到该小组的影响。其中最重要的是该小组的创始人杰伊-福雷斯特(Jay Forrester)。除了杰伊之外,我的老师(以及成为我老师的学生)还包括埃德-罗伯茨(Ed Roberts)、杰克-普(Jack Pugh)、丹尼斯-米多斯(Dennis Meadows)、哈特穆特-博塞尔(Hartmut Bossel)、巴里-里士满(Barry Richmond)、彼得-圣吉(Peter Senge)、约翰-斯特曼(John Sterman)和彼得-艾伦(Peter Allen)。我向所有成员表示钦佩和感谢。
I also have drawn from thinkers in a variety of disciplines, who, as far as I know, never used a computer to simulate a system, but who are natural systems thinkers. They include Gregory Bateson, Kenneth Boulding, Herman Daly, Albert Einstein, Garrett Hardin, Václav Havel, Lewis Mumford, Gunnar Myrdal, E.F. Schumacher, a number of modern corporate executives, and many anonymous sources of ancient wisdom, from Native Americans to the Sufis of the Middle East. Strange bedfellows, but systems thinking transcends disciplines and cultures and, when it is done right, it overarches history as well.
据我所知,他们从未使用过计算机模拟系统,但他们都是自然系统思想家。他们包括格雷戈里-贝特森(Gregory Bateson)、肯尼斯-博尔丁(Kenneth Boulding)、赫尔曼-戴利(Herman Daly)、阿尔伯特-爱因斯坦(Albert Einstein)、加勒特-哈丁(Garrett Hardin)、瓦茨拉夫-哈维尔(Václav Havel)、刘易斯-芒福德(Lewis Mumford)、贡纳尔-米达尔(Gunnar Myrdal)、E.F. 舒马赫(E.F. Schumacher)、一些现代企业高管,以及从美洲原住民到中东苏菲派等许多无名的古代智慧来源。这些都是奇怪的伙伴,但系统思维超越了学科和文化,如果运用得当,它还能超越历史。
Having spoken of transcendence, I need to acknowledge factionalism as well. Systems analysts use overarching concepts, but they have entirely human personalities, which means that they have formed many fractious schools of systems thought. I have used the language and symbols of system dynamics here, the school in which I was taught. And I present only the core of systems theory here, not the leading edge. I don't deal with the most abstract theories and am interested in analysis only when I can see how it helps solve real problems. When the abstract end of systems theory does that, which I believe it will some day, another book will have to be written.
Therefore, you should be warned that this book, like all books, is biased and incomplete. There is much, much more to systems thinking than is

presented here, for you to discover if you are interested. One of my purposes is to make you interested. Another of my purposes, the main one, is to give you a basic ability to understand and to deal with complex systems, even if your formal systems training begins and ends with this book.


In 1993, Donella (Dana) Meadows completed a draft of the book you now hold. The manuscript was not published at the time, but circulated informally for years. Dana died quite unexpectedly in 2001-before she completed this book. In the years since her death, it became clear that her writings have continued to be useful to a wide range of readers. Dana was a scientist and writer, and one of the best communicators in the world of systems modeling.
1993 年,Donella (Dana) Meadows 完成了您现在手中这本书的草稿。手稿当时没有出版,但非正式流传了多年。2001 年,丹娜在完成这本书之前意外去世。在她去世后的这些年里,我们发现她的著作对广大读者仍然有用。丹娜是一位科学家和作家,也是系统建模领域最优秀的传播者之一。
In 1972, Dana was lead author of The Limits to Growth - a best-selling and widely translated book. The cautions she and her fellow authors issued then are recognized today as the most accurate warnings of how unsustainable patterns could, if unchecked, wreak havoc across the globe. That book made headlines around the world for its observations that continual growth in population and consumption could severely damage the ecosystems and social systems that support life on earth, and that a drive for limitless economic growth could eventually disrupt many local, regional, and global systems. The findings in that book and its updates are, once again, making front-page news as we reach peak oil, face the realities of climate change, and watch a world of 6.6 billion people deal with the devastating consequences of physical growth.
1972 年,丹娜是畅销书《增长的极限》(The Limits to Growth)的主要作者,该书被广泛翻译。她和其他作者当时发出的警告被认为是最准确的警示,告诉人们如果不加以控制,不可持续的模式会给全球带来怎样的灾难。这本书成为了全世界的头条新闻,因为书中指出,人口和消费的持续增长可能会严重破坏支持地球生命的生态系统和社会系统,无限的经济增长动力最终可能会破坏许多地方、地区和全球系统。随着石油峰值的到来,面对气候变化的现实,以及眼看着一个拥有 66 亿人口的世界要应对物质增长带来的破坏性后果,该书及其更新版中的发现再次成为头版新闻。
In short, Dana helped usher in the notion that we have to make a major shift in the way we view the world and its systems in order to correct our course. Today, it is widely accepted that systems thinking is a critical tool in addressing the many environmental, political, social, and economic challenges we face around the world. Systems, big or small, can behave in similar ways, and understanding those ways is perhaps our best hope for making lasting change on many levels. Dana was writing this book to bring that concept to a wider audience, and that is why I and my colleagues at the Sustainability Institute decided it was time to publish her manuscript posthumously.
Will another book really help the world and help you, the reader? I think

so. Perhaps you are working in a company (or own a company) and are struggling to see how your business or organization can be part of a shift toward a better world. Or maybe you're a policy maker who is seeing others "push back" against your good ideas and good intentions. Perhaps you're a manager who has worked hard to fix some important problems in your company or community, only to see other challenges erupt in their wake. As one who advocates for changes in how a society (or a family) functions, what it values and protects, you may see years of progress easily undone in a few swift reactions. As a citizen of an increasingly global society, perhaps you are just plain frustrated with how hard it is to make a positive and lasting difference.
所以。也许你在一家公司工作(或拥有一家公司),正在苦苦思索你的企业或组织如何才能成为向更美好世界转变的一部分。又或者,你是一位政策制定者,看到别人 "回击 "你的好想法和好意图。也许你是一位管理者,努力解决了公司或社区的一些重要问题,但却看到其他挑战随之而来。作为一个倡导改变社会(或家庭)运作方式、价值观念和保护措施的人,你可能会看到多年来取得的进步很容易被一些迅速的反应所抵消。作为一个日益全球化的社会的公民,也许你只是单纯地感到沮丧,因为要做出积极而持久的改变是多么困难。
If so, I think that this book can help. Although one can find dozens of titles on "systems modeling" and "systems thinking," there remains a clear need for an approachable and inspiring book about systems and us-why we find them at times so baffling and how we can better learn to manage and redesign them.
如果是这样,我想这本书会有所帮助。尽管我们可以找到几十种关于 "系统建模 "和 "系统思考 "的书籍,但我们仍然明显需要一本关于系统和我们的平易近人、鼓舞人心的书籍--为什么我们有时会发现它们如此令人困惑,以及我们如何才能更好地学会管理和重新设计它们。
At the time that Dana was writing Thinking in Systems, she had recently completed the twenty-year update to Limits to Growth, titled Beyond the Limits. She was a Pew Scholar in Conservation and the Environment, was serving on the Committee on Research and Exploration for the National Geographic Society, and she was teaching about systems, environment, and ethics at Dartmouth College. In all aspects of her work, she was immersed in the events of the day. She understood those events to be the outward behavior of often complex systems.
Although Dana's original manuscript has been edited and restructured, many of the examples you will find in this book are from her first draft in 1993. They may seem a bit dated to you, but in editing her work I chose to keep them because their teachings are as relevant now as they were then. The early 1990s were the time of the dissolution of the Soviet Union and great shifts in other socialist countries. The North American Free Trade Agreement was newly signed. Iraq's army invaded Kuwait and then retreated, burning oil fields on the way out. Nelson Mandela was freed from prison, and South Africa's apartheid laws were repealed. Labor leader Lech Walesa was elected president of Poland, and poet Václav Havel was elected president of Czechoslovakia. The International Panel on Climate Change issued its first assessment report, concluding that "emissions from human activities are substantially increasing the atmospheric concentra-
虽然达娜的原稿已经过编辑和调整,但你在本书中看到的许多例子都来自她 1993 年的初稿。你可能会觉得这些例子有些过时,但在编辑她的作品时,我选择了保留它们,因为它们的教诲现在和当时一样具有现实意义。20 世纪 90 年代初,苏联解体,其他社会主义国家也发生了巨大变化。北美自由贸易协定》刚刚签署。伊拉克军队入侵科威特,随后撤退,途中焚烧油田。纳尔逊-曼德拉获释出狱,南非种族隔离法被废除。工党领袖莱赫-瓦文萨当选波兰总统,诗人瓦茨拉夫-哈维尔当选捷克斯洛伐克总统。国际气候变化专门委员会发布了第一份评估报告,得出结论认为 "人类活动的排放正在大幅增加大气中的温室气体浓度"。

tions of greenhouse gases and that this will enhance the greenhouse effect and result in an additional warming of the Earth's surface." The UN held a conference in Rio de Janeiro on environment and development.
While traveling to meetings and conferences during this time, Dana read the International Herald Tribune and during a single week found many examples of systems in need of better management or complete redesign. She found them in the newspaper because they are all around us every day. Once you start to see the events of the day as parts of trends, and those trends as symptoms of underlying system structure, you will be able to consider new ways to manage and new ways to live in a world of complex systems. In publishing Dana's manuscript, I hope to increase the ability of readers to understand and talk about the systems around them and to act for positive change.
I hope this small approachable introduction to systems and how we think about them will be a useful tool in a world that rapidly needs to shift behaviors arising from very complex systems. This is a simple book for and about a complex world. It is a book for those who want to shape a better future.
-Diana Wright, 2008 戴安娜-赖特,2008 年
If a factory is torn down but the rationality which produced it is left standing, then that rationality will simply produce another factory. If a revolution destroys a government, but the systematic patterns of thought that produced that government are left intact, then those patterns will repeat themselves.... There's so much talk about the system. And so little understanding.
-Robert Pirsig, Zen and the Art of Motorcycle Maintenance

Introduction: The System Lens

Managers are not confronted with problems that are independent of each other, but with dynamic situations that consist of complex systems of changing problems that interact with each other. I call such situations messes. . . . Managers do not solve problems, they manage messes.
管理者面临的问题并不是相互独立的,而是由不断变化的问题组成的复杂系统相互作用的动态局面。我把这种情况称为 "混乱"。. . .管理者不是解决问题,而是管理混乱。
—Russell AcкоғF, operations theorist
-Russell AcкоғF, 运筹学理论家
Early on in teaching about systems, I often bring out a Slinky. In case you grew up without one, a Slinky is a toy-a long, loose spring that can be made to bounce up and down, or pour back and forth from hand to hand, or walk itself downstairs.
在系统教学的初期,我经常会拿出一个弹簧球。如果你从小到大都没有玩过,那么 "弹簧狗 "就是一种玩具--一种长长的、松散的弹簧,它可以上下跳动,也可以在手中来回弹动,还可以自己走下楼去。
I perch the Slinky on one upturned palm. With the fingers of the other hand, I grasp it from the top, partway down its coils. Then I pull the bottom hand away. The lower end of the Slinky drops, bounces back up again, yo-yos up and down, suspended from my fingers above.
"What made the Slinky bounce up and down like that?" I ask students.
"Your hand. You took away your hand," they say.
So I pick up the box the Slinky came in and hold it the same way, poised on a flattened palm, held from above by the fingers of the other hand. With as much dramatic flourish as I can muster, I pull the lower hand away.
Nothing happens. The box just hangs there, of course.
"Now once again. What made the Slinky bounce up and down?"
The answer clearly lies within the Slinky itself. The hands that manipulate it suppress or release some behavior that is latent within the structure of the spring.
That is a central insight of systems theory.
Once we see the relationship between structure and behavior, we can begin to understand how systems work, what makes them produce poor results, and how to shift them into better behavior patterns. As our world

continues to change rapidly and become more complex, systems thinking will help us manage, adapt, and see the wide range of choices we have before us. It is a way of thinking that gives us the freedom to identify root causes of problems and see new opportunities.
So, what is a system? A system is a set of things-people, cells, molecules, or whatever-interconnected in such a way that they produce their own pattern of behavior over time. The system may be buffeted, constricted, triggered, or driven by outside forces. But the system's response to these forces is characteristic of itself, and that response is seldom simple in the real world.
When it comes to Slinkies, this idea is easy enough to understand. When it comes to individuals, companies, cities, or economies, it can be heretical. The system, to a large extent, causes its own behavior! An outside event may unleash that behavior, but the same outside event applied to a different system is likely to produce a different result.
说到 "弹弓",这种想法很容易理解。但如果涉及到个人、公司、城市或经济,这可能就是异端邪说了。在很大程度上,系统是自身行为的根源!外部事件可能会引发这种行为,但同样的外部事件应用到不同的系统中,很可能会产生不同的结果。
Think for a moment about the implications of that idea:
  • Political leaders don't cause recessions or economic booms. Ups and downs are inherent in the structure of the market economy.
  • Competitors rarely cause a company to lose market share. They may be there to scoop up the advantage, but the losing company creates its losses at least in part through its own business policies.
  • The oil-exporting nations are not solely responsible for oilprice rises. Their actions alone could not trigger global price rises and economic chaos if the oil consumption, pricing, and investment policies of the oil-importing nations had not built economies that are vulnerable to supply interruptions.
  • The flu virus does not attack you; you set up the conditions for it to flourish within you.
  • Drug addiction is not the failing of an individual and no one person, no matter how tough, no matter how loving, can cure a drug addict—not even the addict. It is only through understanding addiction as part of a larger set of influences and societal issues that one can begin to address it.
Something about statements like these is deeply unsettling. Something else is purest common sense. I submit that those two somethings-a resistance to and a recognition of systems principles-come from two kinds of human experience, both of which are familiar to everyone.
On the one hand, we have been taught to analyze, to use our rational ability, to trace direct paths from cause to effect, to look at things in small and understandable pieces, to solve problems by acting on or controlling the world around us. That training, the source of much personal and societal power, leads us to see presidents and competitors, OPEC and the flu and drugs as the causes of our problems.
On the other hand, long before we were educated in rational analysis, we all dealt with complex systems. We are complex systems-our own bodies are magnificent examples of integrated, interconnected, self-maintaining complexity. Every person we encounter, every organization, every animal, garden, tree, and forest is a complex system. We have built up intuitively, without analysis, often without words, a practical understanding of how these systems work, and how to work with them.
Modern systems theory, bound up with computers and equations, hides the fact that it traffics in truths known at some level by everyone. It is often possible, therefore, to make a direct translation from systems jargon to traditional wisdom.
Because of feedback delays within complex systems, by the time a problem becomes apparent it may be unnecessarily difficult to solve.
  • A stitch in time saves nine.
According to the competitive exclusion principle, if a reinforcing feedback loop rewards the winner of a competition with the means to win further competitions, the result will be the elimination of all but a few competitors.
  • For he that hath, to him shall be given; and he that hath not, from him shall be taken even that which he hath (Mark 4:25) or
    因为有的,要赐给他;没有的,连他所有的也要夺过来(马可福音 4:25)或
-The rich get richer and the poor get poorer.
A diverse system with multiple pathways and redundancies is

more stable and less vulnerable to external shock than a uniform system with little diversity.
  • Don't put all your eggs in one basket.
Ever since the Industrial Revolution, Western society has benefited from science, logic, and reductionism over intuition and holism. Psychologically and politically we would much rather assume that the cause of a problem is "out there," rather than "in here." It's almost irresistible to blame something or someone else, to shift responsibility away from ourselves, and to look for the control knob, the product, the pill, the technical fix that will make a problem go away.
自工业革命以来,西方社会一直受益于科学、逻辑和还原论,而非直觉和整体论。在心理上和政治上,我们更愿意假设问题的原因在 "外面",而不是 "这里"。将问题归咎于某物或他人,将责任从自己身上转移开,寻找能让问题消失的控制钮、产品、药片和技术解决方案,这几乎是不可抗拒的。
Serious problems have been solved by focusing on external agentspreventing smallpox, increasing food production, moving large weights and many people rapidly over long distances. Because they are embedded in larger systems, however, some of our "solutions" have created further problems. And some problems, those most rooted in the internal structure of complex systems, the real messes, have refused to go away.
通过对外部因素的关注,一些严重的问题已经得到了解决,如预防天花、提高粮食产量、长距离快速移动重物和人员等。然而,由于这些问题蕴含在更大的系统中,我们的一些 "解决方案 "造成了更多的问题。而有些问题,那些最根植于复杂系统内部结构的问题,那些真正的混乱,却一直不肯消失。
Hunger, poverty, environmental degradation, economic instability, unemployment, chronic disease, drug addiction, and war, for example, persist in spite of the analytical ability and technical brilliance that have been directed toward eradicating them. No one deliberately creates those problems, no one wants them to persist, but they persist nonetheless. That is because they are intrinsically systems problems-undesirable behaviors characteristic of the system structures that produce them. They will yield only as we reclaim our intuition, stop casting blame, see the system as the source of its own problems, and find the courage and wisdom to restructure it.
Obvious. Yet subversive. An old way of seeing. Yet somehow new. Comforting, in that the solutions are in our hands. Disturbing, because we must do things, or at least see things and think about things, in a different way.
This book is about that different way of seeing and thinking. It is intended for people who may be wary of the word "systems" and the field of systems analysis, even though they may have been doing systems thinking all their lives. I have kept the discussion nontechnical because I want to show what a long way you can go toward understanding systems without turning to mathematics or computers.
本书讲述的就是这种不同的观察和思考方式。本书的读者可能对 "系统 "一词和系统分析领域心存戒备,尽管他们可能一生都在进行系统思考。我之所以保持非技术性的讨论,是因为我想向读者展示,不借助数学或计算机,你也可以在理解系统方面走得很远。
I have made liberal use of diagrams and time graphs in this book

because there is a problem in discussing systems only with words. Words and sentences must, by necessity, come only one at a time in linear, logical order. Systems happen all at once. They are connected not just in one direction, but in many directions simultaneously. To discuss them properly, it is necessary somehow to use a language that shares some of the same properties as the phenomena under discussion.
Pictures work for this language better than words, because you can see all the parts of a picture at once. I will build up systems pictures gradually, starting with very simple ones. I think you'll find that you can understand this graphical language easily.
I start with the basics: the definition of a system and a dissection of its parts (in a reductionist, unholistic way). Then I put the parts back together to show how they interconnect to make the basic operating unit of a system: the feedback loop.
Next I will introduce you to a systems zoo-a collection of some common and interesting types of systems. You'll see how a few of these creatures behave and why and where they can be found. You'll recognize them; they're all around you and even within you.
With a few of the zoo "animals"—a set of specific examples-as a foundation, I'll step back and talk about how and why systems work so beautifully and the reasons why they so often surprise and confound us. I'll talk about why everyone or everything in a system can act dutifully and rationally, yet all these well-meaning actions too often add up to a perfectly terrible result. And why things so often happen much faster or slower than everyone thinks they will. And why you can be doing something that has always worked and suddenly discover, to your great disappointment, that your action no longer works. And why a system might suddenly, and without warning, jump into a kind of behavior you've never seen before.
有了动物园里的几种 "动物"--一组具体的例子--作为基础,我将退后一步,谈谈系统是如何以及为什么能如此完美地运作,以及它们常常让我们感到惊讶和困惑的原因。我将谈谈为什么系统中的每个人或每件事都能尽职尽责、理性行事,但所有这些善意的行为却往往会导致非常糟糕的结果。为什么事情发生的速度往往比每个人想象的要快得多或慢得多。为什么你在做一件一直有效的事情时,会突然失望地发现你的行动不再有效了?还有,为什么一个系统会在毫无征兆的情况下,突然出现一种你从未见过的行为。
That discussion will lead to us to look at the common problems that the systems-thinking community has stumbled upon over and over again through working in corporations and governments, economies and ecosystems, physiology and psychology. "There's another case of the tragedy of the commons," we find ourselves saying as we look at an allocation system for sharing water resource among communities or financial resources among schools. Or we identify "eroding goals" as we study the business rules and incentives that help or hinder the development of new technologies. Or we see "policy resistance" as we examine decision-making power and the nature of relationships in a
这一讨论将引导我们审视系统思考界在企业和政府、经济和生态系统、生理学和心理学等领域工作时一再发现的共同问题。"当我们研究社区间共享水资源或学校间共享财政资源的分配制度时,我们发现自己在说:"这又是一个公地悲剧的案例。或者,当我们研究有助于或阻碍新技术发展的商业规则和激励措施时,我们会发现 "目标正在被侵蚀"。或者,当我们研究决策权和关系性质时,我们会看到 "政策阻力"。

family, a community, or a nation. Or we witness "addiction"—which can be caused by many more agents than caffeine, alcohol, nicotine, and narcotics.
家庭、社区或国家。或者,我们目睹了 "成瘾"--除了咖啡因、酒精、尼古丁和毒品之外,还有许多其他物质也会导致成瘾。
Systems thinkers call these common structures that produce characteristic behaviors "archetypes." When I first planned this book, I called them "system traps." Then I added the words "and opportunities," because these archetypes, which are responsible for some of the most intransigent and potentially dangerous problems, also can be transformed, with a little systems understanding, to produce much more desirable behaviors.
系统思想家把这些产生特征行为的常见结构称为 "原型"。在我最初策划本书时,我称它们为 "系统陷阱"。后来我又加上了 "和机遇 "几个字,因为这些原型造成了一些最顽固、最具潜在危险性的问题,但只要对系统稍加了解,它们也可以转变,产生更理想的行为。
From this understanding I move into what you and I can do about restructuring the systems we live within. We can learn how to look for leverage points for change.
I conclude with the largest lessons of all, the ones derived from the wisdom shared by most systems thinkers I know. For those who want to explore systems thinking further, the Appendix provides ways to dig deeper into the subject with a glossary, a bibliography of systems thinking resources, a summary list of systems principles, and equations for the models described in Part One.
When our small research group moved from MIT to Dartmouth College years ago, one of the Dartmouth engineering professors watched us in seminars for a while, and then dropped by our offices. "You people are different," he said. "You ask different kinds of questions. You see things I don't see. Somehow you come at the world in a different way. How? Why?"
That's what I hope to get across throughout this book, but especially in its conclusion. I don't think the systems way of seeing is better than the reductionist way of thinking. I think it's complementary, and therefore revealing. You can see some things through the lens of the human eye, other things through the lens of a microscope, others through the lens of a telescope, and still others through the lens of systems theory. Everything seen through each kind of lens is actually there. Each way of seeing allows our knowledge of the wondrous world in which we live to become a little more complete.
At a time when the world is more messy, more crowded, more interconnected, more interdependent, and more rapidly changing than ever before, the more ways of seeing, the better. The systems-thinking lens allows us to reclaim our intuition about whole systems and - see interconnections

- ask "what-if" questions about possible future behaviors, and
- 就未来可能出现的行为提出 "假设 "问题,以及

- be creative and courageous about system redesign.
- 勇于创新,大胆进行系统重新设计。
Then we can use our insights to make a difference in ourselves and our world.

INTERLUDE The Blind Men and the Matter of the Elephant
间奏曲 《盲人摸象记

Beyond Ghor, there was a city. All its inhabitants were blind. A king with his entourage arrived nearby; he brought his army and camped in the desert. He had a mighty elephant, which he used to increase the people's awe.
The populace became anxious to see the elephant, and some sightless from among this blind community ran like fools to find it.
As they did not even know the form or shape of the elephant, they groped sightlessly, gathering information by touching some part of it.
Each thought that he knew something, because he could feel a part.... The man whose hand had reached an ear . . . said: "It is a large, rough thing, wide and broad, like a rug."
每个人都以为自己知道些什么,因为他能感觉到一部分....那个手伸向耳朵的人说"这是一个又大又粗糙的东西 又宽又阔,就像一块地毯"
And the one who had felt the trunk said: "I have the real facts about it. It is like a straight and hollow pipe, awful and destructive."
The one who had felt its feet and legs said: "It is mighty and firm, like a pillar."
Each had felt one part out of many. Each had perceived it wrongly. ... This ancient Sufi story was told to teach a simple lesson but one that we often ignore: The behavior of a system cannot be known just by knowing the elements of which the system is made.
每个人都感受到了其中的一部分。每个人都有错误的认识。... 讲述这个古老的苏菲故事是为了给我们上一堂简单的课,但我们却常常忽略了这一课:仅仅了解构成系统的元素是无法知道系统的行为的。

The Basics 基础知识

I have yet to see any problem, however complicated, which, when looked at in the right way, did not become still more complicated.
一Poul Anderson  一 普尔-安德森

More Than the Sum of Its Parts

A system isn't just any old collection of things. A system is an interconnected set of elements that is coherently organized in a way that achieves something. If you look at that definition closely for a minute, you can see that a system must consist of three kinds of things: elements, interconnections, and a function or purpose.
系统并不只是各种事物的旧集合。一个系统 是一组相互关联的元素,它们以某种方式连贯地组织起来,从而达到某种目的。如果你仔细研究一下这个定义,就会发现一个系统必须由三种东西组成:元素、相互联系以及功能或目的。
For example, the elements of your digestive system include teeth, enzymes, stomach, and intestines. They are interrelated through the physi flow of food, and through an elegant set of regulating chemical signals. The function of this system is to break down food into its basic nutrients and to transfer those nutrients into the bloodstream (another system), while discarding unusable wastes.
例如,消化系统的要素包括牙齿、酶、胃和肠。它们通过生理 食物流和一套优雅的化学调节信号相互关联。这个系统的功能是将食物分解成基本的营养物质,并将这些营养物质输送到血液中(另一个系统),同时丢弃无法使用的废物。
A football team is a system with elements such as players, coach, field, and ball. Its interconnections are the rules of the game, the coach's strategy, the players' communications, and the laws of physics that govern the motions of ball and players. The purpose of the team is to win games, or have fun, or get exercise, or make millions of dollars, or all of the above.
A school is a system. So is a city, and a factory, and a corporation, and a national economy. An animal is a system. A tree is a system, and a forest is a larger system that encompasses subsystems of trees and animals. The earth is a system. So is the solar system; so is a galaxy. Systems can be embedded in systems, which are embedded in yet other systems.
Is there anything that is not a system? Yes-a conglomeration without any particular interconnections or function. Sand scattered on a road by happenstance is not, itself, a system. You can add sand or take away sand and you still have just sand on the road. Arbitrarily add or take away football players, or pieces of your digestive system, and you quickly no longer have the same system.
When a living creature dies, it loses its "system-ness." The multiple interrelations that held it together no longer function, and it dissipates, although its material remains part of a larger
当生物死亡时,它就失去了 "系统性"。维系它的多重相互关系不再起作用,它也随之消散,尽管它的物质仍是更大系统的一部分。
A system is more than the sum of its parts. It may exhibit adaptive, dynamic, goal-seking, self-preserving, and sometimes evolutionary behavior. food-web system. Some people say that an old city neighborhood where people know each other and communicate regularly is a social system, and that a new apartment block full of strangers is not-not until new relationships arise and a system forms.
You can see from these examples that there is an integrity or wholeness about a system and an active set of mechanisms to maintain that integrity. Systems can change, adapt, respond to events, seek goals, mend injuries, and attend to their own survival in lifelike ways, although they may contain or consist of nonliving things. Systems can be self-organizing, and often are self-repairing over at least some range of disruptions. They are resilient, and many of them are evolutionary. Out of one system other completely new, never-beforeimagined systems can arise.

Look Beyond the Players to the Rules of the Game

You think that because you understand "one" that you must therefore understand "two" because one and one make two. But you forget that you must also understand "and."
你以为理解了 "一",就一定能理解 "二",因为一加一等于二。但你忘了,你还必须理解 "和"。
-Sufi teaching story -苏菲教学故事
The elements of a system are often the easiest parts to notice, because many of them are visible, tangible things. The elements that make up a tree are roots, trunk, branches, and leaves. If you look more closely, you


How to know whether you are looking at a system or just a bunch of stuff:
A) Can you identify parts? . . . and
A) 你能识别零件吗?......和
B) Do the parts affect each other? . . . and
B) 各部分是否相互影响?......以及
C) Do the parts together produce an effect that is different from the effect of each part on its own? ... and perhaps
D) Does the effect, the behavior over time, persist in a variety of circumstances?
D) 随着时间的推移,这种效果和行为是否会在各种情况下持续存在?
see specialized cells: vessels carrying fluids up and down, chloroplasts, and so on. The system called a university is made up of buildings, students, professors, administrators, libraries, books, computers-and I could go on and say what all those things are made up of. Elements do not have to be physical things. Intangibles are also elements of a system. In a university, school pride and academic prowess are two intangibles that can be very important elements of the system. Once you start listing the elements of a system, there is almost no end to the process. You can divide elements into sub-elements and then sub-sub-elements. Pretty soon you lose sight of the system. As the saying goes, you can't see the forest for the trees.
我们可以看到专门的细胞:上下输送液体的血管、叶绿体等等。被称为大学的系统由建筑、学生、教授、管理人员、图书馆、书籍、计算机组成--我还可以继续说这些东西是由什么组成的。要素不一定是有形的东西。无形资产也是一个系统的要素。在一所大学中,学校荣誉和学术实力就是两种无形的东西,它们可能是系统中非常重要的元素。一旦开始列出一个系统的要素,这个过程就几乎没有尽头。你可以把要素分为子要素,然后再分为子要素。很快,你就会忽略整个系统。正所谓 "只见树木,不见森林"。
Before going too far in that direction, it's a good idea to stop dissecting out elements and to start looking for the interconnections, the relationships that hold the elements together.
The interconnections in the tree system are the physical flows and chemical reactions that govern the tree's metabolic processes-the signals that allow one part to respond to what is happening in another part. For example, as the leaves lose water on a sunny day, a drop in pressure in the water-carrying vessels allows the roots to take in more water. Conversely, if the roots experience dry soil, the loss of water pressure signals the leaves to close their pores, so as not to lose even more precious water.
As the days get shorter in the temperate zones, a deciduous tree puts forth chemical messages that cause nutrients to migrate out of the leaves into the trunk and roots and that weaken the stems, allowing the leaves to

fall. There even seem to be messages that cause some trees to make repellent chemicals or harder cell walls if just one part of the plant is attacked by insects. No one understands all the relationships that allow a tree to do what it does. That lack of knowledge is not surprising. It's easier to learn about a system's elements than about its interconnections.
In the university system, interconnections include the standards for admission, the requirements for degrees, the examinations and grades, the budgets and money flows, the gossip, and most important, the communication of knowledge that is, presumably, the purpose of the whole system.
Some interconnections in systems are actual physi-
Many of the interconnections in systems operate through the flow of information. Information holds systems together and plays a great role in determining how they operate. cal flows, such as the water in the tree's trunk or the students progressing through a university. Many interconnections are flows of information-signals that go to decision points or action points within a system. These kinds of interconnections are often harder to see, but the system reveals them to those who look. Students may use informal information about the probability of getting a good grade to decide what courses to take. A consumer decides what to buy using information about his or her income, savings, credit rating, stock of goods at home, prices, and availability of goods for purchase. Governments need information about kinds and quantities of water pollution before they can create sensible regulations to reduce that pollution. (Note that information about the existence of a problem may be necessary but not sufficient to trigger action-information about resources, incentives, and consequences is necessary too.)
If information-based relationships are hard to see, functions or purposes are even harder. A system's function or purpose is not necessarily spoken, written, or expressed explicitly, except through the operation of the system. The best way to deduce the system's purpose is to watch for a while to see how the system behaves.
If a frog turns right and catches a fly, and then turns left and catches a fly, and then turns around backward and catches a fly, the purpose of the frog has to do not with turning left or right or backward but with catching flies. If a government proclaims its interest in protecting the environment but allocates little money or effort toward that goal, environmental protection is not, in fact, the government's purpose. Purposes are deduced from behavior, not from rhetoric or stated goals.


The word function is generally used for a nonhuman system, the word purpose for a human one, but the distinction is not absolute, since so many systems have both human and nonhuman elements.
The function of a thermostat-furnace system is to keep a building at a given temperature. One function of a plant is to bear seeds and create more plants. One purpose of a national economy is, judging from its behavior, to keep growing larger. An important function of almost every system is to ensure its own perpetuation.
System purposes need not be human purposes and are not necessarily those intended by any single actor within the system. In fact, one of the most frustrating aspects of systems is that the purposes of subunits may add up to an overall behavior that no one wants. No one intends to produce a society with rampant drug addiction and crime, but consider the combined purposes and consequent actions of the actors involved:
  • desperate people who want quick relief from psychological pain
  • farmers, dealers, and bankers who want to earn money
  • pushers who are less bound by civil law than are the police who oppose them
  • governments that make harmful substances illegal and use police power to interdict them
  • wealthy people living in close proximity to poor people
  • nonaddicts who are more interested in protecting themselves than in encouraging recovery of addicts
Altogether, these make up a system from which it is extremely difficult to eradicate drug addiction and crime.
Systems can be nested within systems. Therefore, there can be purposes within purposes. The purpose of a university is to discover and preserve knowledge and pass it on to new generations. Within the university, the purpose of a student may be to get good grades, the purpose of a professor

may be to get tenure, the purpose of an administrator may be to balance the budget. Any of those sub-purposes could come into conflict with the overall purpose-the student could cheat, the professor could ignore the students in order to publish papers, the administrator could balance the budget by firing professors. Keeping sub-purposes and overall system purposes in harmony is an essential function of successful systems. I'll get back to this point later when we come to hierarchies.
You can understand the relative importance of a system's elements, interconnections, and purposes by imagining them changed one by one. Changing elements usually has the least effect on the system. If you change all the players on a football team, it is still recognizably a football team. (It may play much better or much worse-particular elements in a system can indeed be important.) A tree changes its cells constantly, its leaves every year or so, but it is still essentially the same tree. Your body replaces most of its cells every few weeks, but it goes on being your body. The university has a constant flow of students and a slower flow of professors and administrators, but it is still a university. In fact it is still the same university, distinct in subtle ways from others, just as General Motors and the U.S. Congress somehow maintain their identities even though all their members change. A system generally goes on being itself, changing only slowly if at all, even with complete substitutions of its elements-as long as its interconnections and purposes remain intact.
If the interconnections change, the system may be greatly altered. It may even become unrecognizable, even though the same players are on the team. Change the rules from those of football to those of basketball, and you've got, as they say, a whole new ball game. If you change the interconnections in the tree-say that instead of taking in carbon dioxide and emitting oxygen, it does the reverse-it would no longer be a tree. (It would be an animal.) If in a university the students graded the professors, or if arguments were won by force instead of reason, the place would need a different name. It might be an interesting organization, but it would not be a university. Changing interconnections in a system can change it dramatically.
如果相互联系发生变化,系统可能会发生巨大变化。甚至可能变得面目全非,即使球队中的球员还是那些球员。把足球规则改成篮球规则,就像人们说的那样,你会得到一个全新的球赛。如果你改变了树的相互联系--比如说,它不再吸收二氧化碳和释放氧气,而是反过来--它就不再是一棵树了(它将成为一种动物)。 如果在大学里,学生给教授打分,或者如果争论是以武力而不是理性取胜,那么这个地方就需要一个不同的名字。它可能是一个有趣的组织,但不会是一所大学。改变一个系统中的相互联系可以使其发生巨大变化。
Changes in function or purpose also can be drastic. What if you keep the players and the rules but change the purpose-from winning to losing, for example? What if the function of a tree were not to survive and repro-

duce but to capture all the nutrients in the soil and grow to unlimited size? People have imagined many purposes for a university besides disseminating knowledge-making money, indoctrinating people, winning football games. A change in purpose changes a system profoundly, even if every element and interconnection remains the same.
To ask whether elements, interconnections, or purposes are most important in a system is to ask an unsystemic question. All are essential. All interact. All have their roles. But the least obvious part of the system, its function or purpose, is often the most crucial determinant of the system's behavior. Interconnections are also critically important. Changing relationships usually changes system behavior. The elements, the parts of systems we are most likely to notice, are often (not always) least important in defining the unique characteristics of the system-unless changing an element also results in changing relationships or purpose.
Changing just one leader at the top-from a Brezhnev to a Gorbachev, or from a Carter to a Reagan-may or may not turn an entire nation in a new direction, though its land, factories, and hundreds of millions of people remain exactly the same. A leader can make that land and those factories and people play a different game with new rules, or can direct the play toward a new purpose.
And conversely, because land, factories, and people are long-lived, slowly changing, physical elements of the system, there is a limit to the rate at which any leader can turn the direction of a nation.

Bathtubs 101-Understanding System Behavior over Time
浴缸 101--了解系统随时间变化的行为

Information contained in nature ... allows us a partial reconstruction of the past.... The development of the meanders in a river, the increasing complexity of the earth's crust . . . are information-storing devices in the same manner that genetic systems are.... Storing information means increasing the complexity of the mechanism.
-Ramon Margalef
A stock is the foundation of any system. Stocks are the elements of the system that you can see, feel, count, or measure at any given time. A system stock is just what it sounds like: a store, a quantity, an accumulation of

material or information that has built up over time. It may be the water in a bathtub, a population, the books in a bookstore, the wood in a tree, the money in a bank, your own self-confidence. A stock does not have to be physical. Your reserve of good will toward others
A stock is the memory of the history of changing flows within the system. or your supply of hope that the world can be better are both stocks.
Stocks change over time through the actions of a flow. Flows are filling and draining, births and deaths, purchases and sales, growth and decay, deposits and withdrawals, successes and failures. A stock, then, is the present memory of the history of changing flows within the system.
Figure 1. How to read stock-and-flow diagrams. In this book, stocks are shown as boxes, and flows as arrow-headed "pipes" leading into or out of the stocks. The small T on each flow signifies a "faucet;" it can be turned higher or lower, on or off. The "clouds" stand for wherever the flows come from and go to-the sources and sinks that are being ignored for the purposes of the present discussion.
图 1.如何阅读存量与流量图。在本书中,股票以方框表示,资金流则以带箭头的 "管道 "表示,流入或流出股票。每个流量上的小 T 代表一个 "水龙头",可以调高或调低,打开或关闭。云 "代表流量的来源和去向,也就是本文讨论中忽略的源和汇。
For example, an underground mineral deposit is a stock, out of which comes a flow of ore through mining. The inflow of ore into a mineral deposit is minute in any time period less than eons. So I have chosen to draw (Figure 2) a simplified picture of the system without any inflow. All system diagrams and descriptions are simplified versions of the real world.
例如,地下矿藏是一个存量,通过开采,矿石从这里流出。在任何时间段内,矿石流入矿床的量都是微乎其微的。因此,我选择绘制一幅没有矿石流入的简化系统图(图 2)。所有系统图和描述都是现实世界的简化版。
Figure 2. A stock of minerals depleted by mining.
图 2.因采矿而枯竭的矿物库存。
Water in a reservoir behind a dam is a stock, into which flow rain and river water, and out of which flows evaporation from the reservoir's surface as well as the water discharged through the dam.
Figure 3. A stock of water in a reservoir with multiple inflows and outflows.
图 3.水库中的水量,有多个流入和流出口。
The volume of wood in the living trees in a forest is a stock. Its inflow is the growth of the trees. Its outflows are the natural deaths of trees and the harvest by loggers. The logging harvest flows into another stock, perhaps an inventory of lumber at a mill. Wood flows out of the inventory stock as lumber sold to customers.
Figure 4. A stock of lumber linked to a stock of trees in a forest.
图 4.木材库存与森林中的树木库存相关联。
If you understand the dynamics of stocks and flows-their behavior over time-you understand a good deal about the behavior of complex systems. And if you have had much experience with a bathtub, you understand the dynamics of stocks and flows.
Figure 5. The structure of a bathtub system-one stock with one inflow and one outflow.
图 5 浴缸系统的结构浴缸系统的结构--一个存量,一个流入,一个流出。
Imagine a bathtub filled with water, with its drain plugged up and its faucets turned off-an unchanging, undynamic, boring system. Now

mentally pull the plug. The water runs out, of course. The level of water in the tub goes down until the tub is empty.
Figure 6. Water level in a tub when the plug is pulled.
图 6.拔出塞子时浴缸中的水位。


Systems thinkers use graphs of system behavior to understand trends over time, rather than focusing attention on individual events. We also use behavior-over-time graphs to learn whether the system is approaching a goal or a limit, and if so, how quickly. The variable on the graph may be a stock or a flow. The pattern-the shape of the variable line-is important, as are the points at which that line changes shape or direction. The precise numbers on the axes are often less important.
The horizontal axis of time allows you to ask questions about what came before, and what might happen next. It can help you focus on the time horizon appropriate to the question or problem you are investigating.
Now imagine starting again with a full tub, and again open the drain, but this time, when the tub is about half empty, turn on the inflow faucet so the rate of water flowing in is just equal to that flowing out. What happens?
The amount of water in the tub stays constant at whatever level it had reached when the inflow became equal to the outflow. It is in a state of dynamic equilibrium-its level does not change, although water is continuously flowing through it.

Figure 7. Constant outflow, inflow turned on after 5 minutes, and the resulting changes in the stock of water in the tub.
图 7.恒定流出,5 分钟后开启流入,以及由此导致的浴缸中水存量的变化。
Imagine turning the inflow on somewhat harder while keeping the outflow constant. The level of water in the tub slowly rises. If you then turn the inflow

faucet down again to match the outflow exactly, the water in the tub will stop rising. Turn it down some more, and the water level will fall slowly.
This model of a bathtub is a very simple system with just one stock, one inflow, and one outflow. Over the time period of interest (minutes), I have assumed that evaporation from the tub is insignificant, so I have not included that outflow. All models, whether mental models or mathematical models, are simplifications of the real world. You know all the dynamic possibilities of this bathtub. From it you can deduce several important principles that extend to more complicated systems:
  • As long as the sum of all inflows exceeds the sum of all outflows, the level of the stock will rise.
  • As long as the sum of all outflows exceeds the sum of all inflows, the level of the stock will fall.
  • If the sum of all outflows equals the sum of all inflows, the stock level will not change; it will be held in dynamic equilibrium at whatever level it happened to be when the two sets of flows became equal.
The human mind seems to focus more easily on stocks than on flows. On top of that, when we do focus on flows, we tend to focus on inflows more easily than on outflows. Therefore, we sometimes miss seeing that we can fill a bathtub not only by increasing the inflow rate,
A stock can be increased by decreasing its outflow rate as well as by increasing its inflow rate. There's more than one way to fill a bathtub! but also by decreasing the outflow rate. Everyone understands that you can prolong the life of an oilbased economy by discovering new oil deposits. It seems to be harder to understand that the same result can be achieved by burning less oil. A breakthrough in energy efficiency is equivalent, in its effect on the stock of available oil, to the discovery of a new oil field—although different people profit from it.
Similarly, a company can build up a larger workforce by more hiring, or it can do the same thing by reducing the rates of quitting and firing. These two strategies may have very different costs. The wealth of a nation can be boosted by investment to build up a larger stock of factories and machines. It also can be boosted, often more cheaply, by decreasing the rate at which factories and machines wear out, break down, or are discarded.
You can adjust the drain or faucet of a bathtub-the flows-abruptly, but it is much more difficult to change the level of water-the stockquickly. Water can't run out the drain instantly, even if you open the drain all the way. The tub can't fill up immediately, even with the inflow faucet on full blast. A stock takes time to change, because flows take time to flow. That's a vital point, a key to understanding why systems behave as they do. Stocks usually change slowly. They can act as delays, lags, buffers, ballast, and sources of momentum in a system. Stocks, especially large ones, respond to change, even sudden change, only by gradual filling or emptying.
People often underestimate the inherent momentum of a stock. It takes a long time for populations to grow or stop growing, for wood Stocks generally change to accumulate in a forest, for a reservoir to fill up, slowly, even when the flows into or out of them change suddenly. Therefore, stocks act as delays or buffers or shock absorbers in systems. for a mine to be depleted. An economy cannot build up a large stock of functioning factories and highways and electric plants overnight, even if a lot of money is available. Once an economy has a lot of oil-burning furnaces and automobile engines, it cannot change quickly to furnaces and engines that burn a different fuel, even if the price of oil suddenly changes. It has taken decades to accumulate the stratospheric pollutants that destroy the earth's ozone layer; it will take decades for those pollutants to be removed.
Changes in stocks set the pace of the dynamics of systems. Industrialization cannot proceed faster than the rate at which factories and machines can be constructed and the rate at which human beings can be educated to run and maintain them. Forests can't grow overnight. Once contaminants have accumulated in groundwater, they can be washed out only at the rate of groundwater turnover, which may take decades or even centuries.
The time lags that come from slowly changing stocks can cause problems in systems, but they also can be sources of stability. Soil that has accumulated over centuries rarely erodes all at once. A population that has learned many skills doesn't forget them immediately. You can pump groundwater faster than the rate it recharges for a long time before the aquifer is drawn down far enough to be damaged. The time lags imposed by stocks allow room to maneuver, to experiment, and to revise policies that aren't working.
If you have a sense of the rates of change of stocks, you don't expect things to happen faster than they can happen. You don't give up too soon.
You can use the opportunities presented by a system's momentum to guide it toward a good outcome-much as a judo expert uses the momentum of an opponent to achieve his or her own goals.
There is one more important principle about the role of stocks in systems, a principle that will lead us directly to the concept of feedback. The presence of stocks allows inflows and outflows to be
Stocks allow inflows and outflows to be decoupled and to be independent and temporarily out of balance with each other. independent of each other and temporarily out of balance with each other.
It would be hard to run an oil company if gasoline had to be produced at the refinery at exactly the rate the cars were burning it. It isn't feasible to harvest a forest at the precise rate at which the trees are growing. Gasoline in storage tanks and wood in the forest are both stocks that permit life to proceed with some certainty, continuity, and predictability, even though flows vary in the short term.
Human beings have invented hundreds of stock-maintaining mechanisms to make inflows and outflows independent and stable. Reservoirs enable residents and farmers downriver to live without constantly adjusting their lives and work to a river's varying flow, especially its droughts and floods. Banks enable you temporarily to earn money at a rate different from how you spend. Inventories of products along a chain from distributors to wholesalers to retailers allow production to proceed smoothly although customer demand varies, and allow customer demand to be filled even though production rates vary.
Most individual and institutional decisions are designed to regulate the levels in stocks. If inventories rise too high, then prices are cut or advertising budgets are increased, so that sales will go up and inventories will fall. If the stock of food in your kitchen gets low, you go to the store. As the stock of growing grain rises or fails to rise in the fields, farmers decide whether to apply water or pesticide, grain companies decide how many barges to book for the harvest, speculators bid on future values of the harvest, cattle growers build up or cut down their herds. Water levels in reservoirs cause all sorts of corrective actions if they rise too high or fall too low. The same can be said for the stock of money in your wallet, the oil reserves owned by an oil company, the pile of woodchips feeding a paper mill, and the concentration of pollutants in a lake.
People monitor stocks constantly and make decisions and take actions

designed to raise or lower stocks or to keep them within acceptable ranges. Those decisions add up to the ebbs and flows, successes and problems, of all sorts of systems. Systems thinkers see the world as a collection of stocks along with the mechanisms for regulating the levels in the stocks by manipulating flows.
That means system thinkers see the world as a collection of "feedback processes."
这意味着系统思想家将世界视为 "反馈过程 "的集合。

How the System Runs Itself-Feedback

Systems of information-feedback control are fundamental to all life and human endeavor, from the slow pace of biological evolution to the launching of the latest space satellite. . . . Everything we do as individuals, as an industry, or as a society is done in the context of an information-feedback system.
从缓慢的生物进化到发射最新的太空卫星,信息反馈控制系统是所有生命和人类活动的基础。. . .作为个人、行业或社会,我们所做的一切都离不开信息反馈系统。
— —ay W. Forrester
-ay W. Forrester
When a stock grows by leaps and bounds or declines swiftly or is held within a certain range no matter what else is going on around it, it is likely that there is a control mechanism at work. In other words, if you see a behavior that persists over time, there is likely a mechanism creating that consistent behavior. That mechanism operates through a feedback loop. It is the consistent behavior pattern over a long period of time that is the first hint of the existence of a feedback loop.
A feedback loop is formed when changes in a stock affect the flows into or out of that same stock. A feedback loop can be quite simple and direct. Think of an interest-bearing savings account in a bank. The total amount of money in the account (the stock) affects how much money comes into the account as interest. That is because the bank has a rule that the account earns a certain percent interest each year. The total dollars of interest paid into the account each year (the flow in) is not a fixed amount, but varies with the size of the total in the account.
You experience another fairly direct kind of feedback loop when you get your bank statement for your checking account each month. As your level of available cash in the checking account (a stock) goes down, you may decide to work more hours and earn more money. The money entering

your bank account is a flow that you can adjust in order to increase your stock of cash to a more desirable level. If your bank account then grows very large, you may feel free to work less (decreasing the inflow). This kind of feedback loop is keeping your level of cash available within a range that is acceptable to you. You can see that adjusting your earnings is not the only feedback loop that works on your stock of cash. You also may be able to adjust the outflow of money from your account, for example. You can imagine an outflow-adjusting feedback loop for spending.
Feedback loops can cause stocks to maintain their level within a range or grow or decline. In any case, the flows into or out of the stock are adjusted because of changes in the size of the stock itself. Whoever or whatever is monitoring the stock's level begins a corrective process, adjusting rates of inflow or outflow (or both) and so changing the stock's level. The stock level feeds back through a chain of signals and actions to control itself.

Figure 8. How to read a stock-and-flow diagram with feedback loops. Each diagram distinguishes the stock, the flow that changes the stock, and the information link (shown as a thin, curved arrow) that directs the action. It emphasizes that action or change always proceeds through adjusting flows.
图 8.如何阅读带有反馈回路的存量与流量图。每个图都区分了存量、改变存量的流程以及指导行动的信息链接(以细长的弯曲箭头表示)。它强调了行动或变化总是通过调整流程进行的。
Not all systems have feedback loops. Some systems are relatively simple open-ended chains of stocks and flows. The chain may be affected by outside factors, but the levels of the chain's stocks don't affect its flows. However, those systems that contain feedback loops are common and may be quite elegant or rather surprising, as we shall see.

A feedback loop is a closed chain of causal connections from a stock, through a set of decisions or rules or physical laws or actions that are dependent on the level of the stock, and back again through a flow to change the stock.

Stabilizing Loops-Balancing Feedback

One common kind of feedback loop stabilizes the stock level, as in the checking-account example. The stock level may not remain completely fixed, but it does stay within an acceptable range. What follows are some more stabilizing feedback loops that may be familiar to you. These examples start to detail some of the steps within a feedback loop.
If you're a coffee drinker, when you feel your energy level run low, you may grab a cup of hot black stuff to perk you up again. You, as the coffee drinker, hold in your mind a desired stock level (energy for work). The purpose of this caffeine-delivery system is to keep your actual stock level near or at your desired level. (You may have other purposes for drinking coffee as well: enjoying the flavor or engaging in a social activity.) It is the
Figure 9. Energy level of a coffee drinker.
图 9喝咖啡者的能量水平。

gap, the discrepancy, between your actual and desired levels of energy for work that drives your decisions to adjust your daily caffeine intake.
Notice that the labels in Figure 9, like all the diagram labels in this book, are direction-free. The label says "stored energy in body" not "low energy level," “coffee intake" not "more coffee." That's because feedback loops often can operate in two directions. In this case, the feedback loop can correct an oversupply as well as an undersupply. If you drink too much coffee and find yourself bouncing around with extra energy, you'll lay off the caffeine for a while. High energy creates a discrepancy that says "too much," which then causes you to reduce your coffee intake until your energy level settles down. The diagram is intended to show that the loop works to drive the stock of energy in either direction.
请注意,图 9 中的标签和本书中的所有图表标签一样,是没有方向性的。标签上写的是 "体内储存的能量",而不是 "能量水平低";是 "咖啡摄入量",而不是 "更多的咖啡"。这是因为反馈回路通常可以双向运行。在这种情况下,反馈回路既可以纠正供过于求,也可以纠正供不应求。如果你喝了太多咖啡,发现自己精力充沛,就会暂时停止摄入咖啡因。高能量会产生 "过多 "的差异,从而导致您减少咖啡摄入量,直到能量水平稳定下来。该图旨在说明,这个循环的作用是推动能量存量向任一方向变化。
I could have shown the inflow of energy coming from a cloud, but instead I made the system diagram slightly more complicated. Remember-all system diagrams are simplifications of the real world. We each choose how much complexity to look at. In this example, I drew another stock-the stored energy in the body that can be activated by the caffeine. I did that to indicate that there is more to the system than one simple loop. As every coffee drinker knows, caffeine is only a short-term stimulant. It lets you run your motor faster, but it doesn't refill your personal fuel tank. Eventually the caffeine high wears off, leaving the body more energy-deficient than it was before. That drop could reactivate the feedback loop and generate another trip to the coffee pot. (See the discussion of addiction later in this book.) Or it could activate some longer-term and healthier feedback responses: Eat some food, take a walk, get some sleep.
This kind of stabilizing, goal-seeking, regulating loop is called a balancing feedback loop, so I put a B inside the loop in the diagram. Balancing feedback loops are goal-seeking or stability-seeking. Each tries to keep a stock at a given value or within a range of values. A balancing feedback loop opposes whatever direction of change is imposed on the system. If you push a stock too far up, a balancing loop will try to pull it back down. If you shove it too far down, a balancing loop will try to bring it back up.
这种稳定的、追求目标的调节回路被称为平衡反馈回路,所以我在图中的回路内加了一个 B。平衡反馈回路追求目标或稳定。每个反馈回路都试图将存量保持在给定值或一定范围内。平衡反馈回路反对强加给系统的任何变化方向。如果将股价推得过高,平衡反馈回路就会试图将其拉回来。如果将其推得太低,平衡反馈回路会试图将其拉回来。
Here's another balancing feedback loop that involves coffee, but one that works through physical law rather than human decision. A hot cup of coffee will gradually cool down to room temperature. Its rate of cooling depends on the difference between the temperature of the coffee and the temperature of the room. The greater the difference, the faster the coffee

will cool. The loop works the other way too-if you make iced coffee on a hot day, it will warm up until it has the same temperature as the room. The function of this system is to bring the discrepancy between coffee's temperature and room's temperature to zero, no matter what the direction of the discrepancy.
Figure 10. A cup of coffee cooling (left) or warming (right).
图 10一杯冷却(左)或加热(右)的咖啡。
Starting with coffee at different temperatures, from just below boiling to just above freezing, the graphs in Figure 11 show what will happen to the temperature over time (if you don't drink the coffee). You can see here the "homing" behavior of a balancing feedback loop. Whatever the initial value of the system stock (coffee temperature in this case), whether it is above or below the "goal" (room temperature), the feedback loop brings it toward
图 11 显示了温度随时间变化的情况(如果您不喝咖啡)。在这里,您可以看到平衡反馈回路的 "归位 "行为。无论系统存量(本例中为咖啡温度)的初始值是多少,也无论它是高于还是低于 "目标"(室温),反馈回路都会将其带向 "目标"。
Figure 11. Coffee temperature as it approaches a room temperature of .
图 11.咖啡在接近室温 时的温度。

the goal. The change is faster at first, and then slower, as the discrepancy between the stock and the goal decreases.
This behavior pattern-gradual approach to
Balancingfeedbackloops are equilibrating or goal-seeking structures in systems and are both sources of stability and sources of resistance to change. a system-defined goal- also can be seen when a radioactive element decays, when a missile finds its target, when an asset depreciates, when a reservoir is brought up or down to its desired level, when your body adjusts its blood-sugar concentration, when you pull your car to a stop at a stoplight. You can think of many more examples. The world is full of goal-seeking feedback loops.
The presence of a feedback mechanism doesn't necessarily mean that the mechanism works well. The feedback mechanism may not be strong enough to bring the stock to the desired level. Feedbacks-the interconnections, the information part of the system-can fail for many reasons. Information can arrive too late or at the wrong place. It can be unclear or incomplete or hard to interpret. The action it triggers may be too weak or delayed or resourceconstrained or simply ineffective. The goal of the feedback loop may never be reached by the actual stock. But in the simple example of a cup of coffee, the drink eventually will reach room temperature.

Runaway Loops-Reinforcing Feedback

I'd need rest to refresh my brain, and to get rest it's necessary to travel, and to travel one must have money, and in order to get money you have to work. ...I am in a vicious circle ... from which it is impossible to escape.
—Honoré Balzac, 19th century novelist and playwright
19 世纪小说家和剧作家巴尔扎克
Here we meet a very important feature. It would seem as if this were circular reasoning; profits fell because investment fell, and investment fell because profits fell.
—Jan Tinbergen, economist
-Jan Tinbergen, 经济学家
The second kind of feedback loop is amplifying, reinforcing, self-multiplying, snowballing—a vicious or virtuous circle that can cause healthy growth

or runaway destruction. It is called a reinforcing feedback loop, and will be noted with an in the diagrams. It generates more input to a stock the more that is already there (and less input the less that is already there). A reinforcing feedback loop enhances whatever direction of change is imposed on it.
或失控破坏。这就是所谓的强化反馈回路,在图中将用 标出。它使存量越多,投入就越多(存量越少,投入就越少)。强化反馈回路会增强任何方向的变化。
For example: 例如
  • When we were kids, the more my brother pushed me, the more I pushed him back, so the more he pushed me back, so the more I pushed him back.
  • The more prices go up, the more wages have to go up if people are to maintain their standards of living. The more wages go up, the more prices have to go up to maintain profits. This means that wages have to go up again, so prices go up again.
  • The more rabbits there are, the more rabbit parents there are to make baby rabbits. The more baby rabbits there are, the more grow up to become rabbit parents, to have even more baby rabbits.
  • The more soil is eroded from the land, the less plants are able to grow, so the fewer roots there are to hold the soil, so the more soil is eroded, so less plants can grow.
  • The more I practice piano, the more pleasure I get from the sound, and so the more I play the piano, which gives me more practice.
Reinforcing loops are found wherever a system element has the ability to reproduce itself or to grow as a constant fraction of itself. Those elements include populations and economies. Remember the example of
Figure 12. Interest-bearing bank account.
图 12.计息银行账户。

the interest-bearing bank account? The more money you have in the bank, the more interest you earn, which is added to the money already in the bank, where it earns even more interest.
Figure 13 shows how this reinforcing loop multiplies money, starting with in the bank, and assuming no deposits and no withdrawals over a period of twelve years. The five lines show five different interest rates, from 2 percent to 10 percent per year.
图 13 显示了这个强化循环是如何使资金成倍增长的,从银行中的 开始,假设在 12 年中没有存款也没有取款。五条线表示五种不同的利率,年利率从 2% 到 10%。
Figure 13. Growth in savings with various interest rates.
图 13.不同利率下的储蓄增长情况。
This is not simple linear growth. It is not constant over time. The growth of the bank account at lower interest rates may look linear in the first few years. But, in fact, growth goes faster and faster. The more is there, the more is added. This kind of growth is called "exponential." It's either good news or bad news, depending on what is growing-money in the bank, people
这不是简单的线性增长。它不是长期不变的。银行账户在较低利率下的增长在最初几年可能看起来是线性的。但实际上,增长速度越来越快。存在的越多,增加的就越多。这种增长被称为 "指数增长"。这要么是好消息,要么是坏消息,取决于增长的是什么--银行里的钱,人
Reinforcing feedback loops are self-enhancing, leading to exponential growth or to runaway collapses over time. They are found whenever a stock has the capacity to reinforce or reproduce itself. with HIV/AIDS, pests in a cornfield, a national economy, or weapons in an arms race.
In Figure 14, the more machines and factories (collectively called "capital") you have, the more goods and services ("output") you can produce. The more output you can produce, the more you can invest in new machines and factories. The more you make, the more capacity you have to make even more. This reinforcing feedback loop is the central engine of growth in an economy.
在图 14 中,拥有的机器和工厂(统称为 "资本")越多,就能生产出越多的商品和服务("产出")。产出越多,投资新机器和新工厂的资金就越多。你生产的越多,你就有更大的能力去生产更多。这种不断强化的反馈循环是经济增长的核心动力。
Figure 14. Reinvestment in capital.
图 14.资本再投资。
By now you may be seeing how basic balancing and reinforcing feedback loops are to systems. Sometimes I challenge my students to try to think of any human decision that occurs without a feedback loop-that is, a decision that is made without regard to any information about the level of the stock it influences. Try thinking about that yourself. The more you do, the more you'll begin to see feedback loops everywhere.
The most common "non-feedback" decisions students suggest are falling in love and committing suicide. I'll leave it to you to decide whether you think these are actually decisions made with no feedback involved.
学生们提出的最常见的 "无反馈 "决定是恋爱和自杀。至于你是否认为这些决定实际上是在没有任何反馈的情况下做出的,那就留给你自己去判断吧。
Watch out! If you see feedback loops everywhere, you're already in danger of becoming a systems thinker! Instead of seeing only how A causes B, you'll begin to wonder how B may also influence A-and how A might reinforce or reverse itself. When you hear in the nightly news that the Federal Reserve
小心!如果你看到到处都是反馈回路,那么你就已经有成为系统思考者的危险了!你不会只看到 A 如何导致 B,而是会开始思考 B 如何影响 A,以及 A 如何强化或逆转自身。当你在晚间新闻中听到美联储


Because we bump into reinforcing loops so often, it is handy to know this shortcut: The time it takes for an exponentially growing stock to double in size, the "doubling time," equals approximately 70 divided by the growth rate (expressed as a percentage).
因为我们经常会遇到强化循环,所以知道这个捷径很方便:指数增长的股票规模翻倍所需的时间,即 "翻倍时间",约等于 70 除以增长率(以百分比表示)。
Example: If you put in the bank at interest per year, you will double your money in 10 years . If you get only interest, your money will take 14 years to double.
举例说明:如果您把 存入银行,每年的利息为 ,那么您的钱将在 10 年后翻一番 。如果您只获得 利息,您的钱需要 14 年才能翻一番。
Bank has done something to control the economy, you'll also see that the economy must have done something to affect the Federal Reserve Bank. When someone tells you that population growth causes poverty, you'll ask yourself how poverty may cause population growth.


If causes , is it possible that also causes ?
如果 会导致 ,那么 是否也会导致 呢?
You'll be thinking not in terms of a static world, but a dynamic one. You'll stop looking for who's to blame; instead you'll start asking, "What's the system?" The concept of feedback opens up the idea that a system can cause its own behavior.
你将不再从静态世界的角度思考问题,而是从动态世界的角度思考问题。你将不再追究责任,而是开始追问:"系统是什么?"反馈 "的概念让我们认识到,系统可以导致自己的行为。
So far, I have limited this discussion to one kind of feedback loop at a time. Of course, in real systems feedback loops rarely come singly. They are linked together, often in fantastically complex patterns. A single stock is likely to have several reinforcing and balancing loops of differing strengths pulling it in several directions. A single flow may be adjusted by the contents of three or five or twenty stocks. It may fill one stock while it drains another and feeds into decisions that alter yet another. The many feedback loops in a system tug against each other, trying to make stocks grow, die off, or come into balance with each other. As a result, complex systems do much more than stay steady or explode exponentially or approach goals smoothly-as we shall see.

A Brief Visit to the Systems Zoo

The ... goal of all theory is to make the . . . basic elements as simple and as few as possible without having to surrender the adequate representation of ... experience.
—Albert Einstein, physicist
-阿尔伯特-爱因斯坦, 物理学家
One good way to learn something new is through specific examples rather than abstractions and generalities, so here are several common, simple but important examples of systems that are useful to understand in their own right and that will illustrate many general principles of complex systems.
This collection has some of the same strengths and weaknesses as a zoo. It gives you an idea of the large variety of systems that exist in the world, but it is far from a complete representation of that variety. It groups the animals by family-monkeys here, bears there (single-stock systems here, two-stock systems there)—so you can observe the characteristic behaviors of monkeys, as opposed to bears. But, like a zoo, this collection is too neat. To make the animals visible and understandable, it separates them from each other and from their normal concealing environment. Just as zoo animals more naturally occur mixed together in ecosystems, so the systems animals described here normally connect and interact with each other and with others not illustrated hereall making up the buzzing, hooting, chirping, changing complexity in which we live.
这套书与动物园有一些相同的优缺点。 它让你了解到世界上存在着种类繁多的系统,但它远不能完全代表这些种类。它将动物按家族分组--这里是猴子,那里是熊(这里是单股系统,那里是双股系统)--因此你可以观察到猴子的特征行为,而不是熊的特征行为。但是,就像动物园一样,这套书过于整齐。为了让动物们看得见、摸得着,它把它们彼此分开,也把它们从正常的隐蔽环境中分离出来。就像动物园里的动物更自然地混杂在生态系统中一样,这里描述的系统动物通常也会相互联系、相互作用,并与其他未在此图示的动物一起构成我们生活的嗡嗡声、鸣叫声、啁啾声和不断变化的复杂环境。
Ecosystems come later. For the moment, let's look at one system animal at a time.

One-Stock Systems 单库存系统

A Stock with Two Competing Balancing Loops-a Thermostat

You already have seen the "homing in" behavior of the goal-seeking balancing feedback loop-the coffee cup cooling. What happens if there are two such loops, trying to drag a single stock toward two different goals?
您已经看到了寻求目标的平衡反馈回路的 "归位 "行为--咖啡杯冷却。如果有两个这样的回路,试图将一只股票拖向两个不同的目标,会发生什么情况呢?
One example of such a system is the thermostat mechanism that regulates the heating of your room (or cooling, if it is connected to an air conditioner instead of a furnace). Like all models, the representation of a thermostat in Figure 15 is a simplification of a real home heating system.
这种系统的一个例子就是调节房间供暖(或制冷,如果连接的是空调而不是火炉)的自动调温器。与所有模型一样,图 15 中的自动调温器也是对真实家庭供暖系统的简化。
Figure 15. Room temperature regulated by a thermostat and furnace.
图 15.室温由恒温器和炉子调节。
Whenever the room temperature falls below the thermostat setting, the thermostat detects a discrepancy and sends a signal that turns on the heat flow from the furnace, warming the room. When the room temperature rises again, the thermostat turns off the heat flow. This straightforward, stock-maintaining, balancing feedback loop is shown on the left side of Figure 15. If there were nothing else in the system, and if you start with a cold room with the thermostat set at , it would behave as shown in Figure 16. The furnace comes on, and the room warms up. When the room temperature reaches the thermostat setting, the furnace goes off, and the room stays right at the target temperature.
每当室温低于自动调温器的设定值时,自动调温器就会检测到差异并发出信号,从而开启火炉的热流,使室内升温。当室温再次升高时,自动调温器就会关闭热流。图 15 左侧显示了这一简单明了的库存维持平衡反馈回路。如果系统中没有任何其他设备,并且开始时房间很冷,恒温器的温度设定为 ,则系统的运行情况如图 16 所示。电炉开始工作,室内温度升高。当室温达到恒温器的设定值时,火炉熄灭,室内温度保持在目标温度。
However, this is not the only loop in the system. Heat also leaks to the outside. The outflow of heat is governed by the second balancing feedback loop, shown on the right side of Figure 15. It is always trying to make the room temperature equal to the outside, just like a coffee cup cooling. If
然而,这并不是系统中唯一的回路。热量也会向外泄漏。热量的流出由第二个平衡反馈回路控制,如图 15 右侧所示。它一直在努力使室温与室外温度相等,就像咖啡杯冷却一样。如果
Figure 16. A cold room warms quickly to the thermostat setting.
图 16.寒冷的房间会迅速升温至恒温器设定值。
Figure 17. A warm room cools very slowly to the outside temperature of .
图 17.温暖的房间缓慢冷却到室外温度
this were the only loop in the system (if there were no furnace), Figure 17 shows what would happen, starting with a warm room on a cold day.
如果系统中只有这个环路(如果没有炉子),图 17 显示了在寒冷的天气里从一个温暖的房间开始时会发生的情况。
The assumption is that room insulation is not perfect, and so some heat leaks out of the warm room to the cool outdoors. The better the insulation, the slower the drop in temperature would be.
Now, what happens when these two loops operate at the same time? Assuming that there is sufficient insulation and a properly sized furnace, the heating loop dominates the cooling loop. You end up with a warm room (see Figure 18), even starting with a cold room on a cold day.
那么,当这两个回路同时运行时会发生什么情况呢?假设有足够的隔热材料和大小合适的炉子,那么供热环路将主导制冷环路。即使是在寒冷的天气里,从一个寒冷的房间开始,最终也会有一个温暖的房间(见图 18)。
Figure 18. The furnace warms a cool room, even as heat continues to leak from the room.
图 18.炉子为凉爽的房间供暖,但房间内的热量仍在继续泄漏。
As the room heats up, the heat flowing out of it increases, because there's a larger gap between inside and outside temperatures. But the furnace keeps putting in more heat than the amount that leaks out, so the room warms nearly to the target temperature. At that point, the furnace cycles off and on as it compensates for the heat constantly flowing out of the room.
The thermostat is set at in this simulation, but the room temperature levels off slightly below . That's because of the leak to the outside, which is draining away some heat even as the furnace is getting the signal to put it back. This is a characteristic and sometimes surprising behavior of a system with competing balancing loops. It's like trying to keep a bucket full when there's a hole in the bottom. To make things worse, water leaking out of the hole is governed by a feedback loop; the more water in the bucket, the more the water pressure at the hole increases, so the flow out increases! In this case, we are trying to keep the room warmer than the outside and the warmer the room is, the faster it loses heat to the outside. It takes time for the furnace to correct for the increased heat loss-and in that minute still more heat leaks out. In a well-insulated house, the leak will be slower and so the house more comfortable than a poorly insulated one, even a poorly insulated house with a big furnace.
在此模拟中,恒温器的设定温度为 ,但室温略低于 。这是因为向室外泄漏了一些热量,甚至在炉子收到重新放热的信号时,热量也被排走了。这是有相互竞争的平衡回路的系统所特有的行为,有时会令人吃惊。这就好比桶底有个洞,却要把桶装满。更糟糕的是,从洞口漏出的水是受反馈回路控制的;桶里的水越多,洞口的水压就越大,因此流出的水也就越多!在这种情况下,我们试图让室内温度高于室外,而室内温度越高,向室外散失热量的速度就越快。炉子需要时间来修正增加的热量损失,而在这一分钟内,还会有更多的热量泄漏出去。在隔热性能良好的房屋中,热量泄漏的速度会更慢,因此房屋会比隔热性能差的房屋更舒适,即使是使用大火炉的隔热性能差的房屋也是如此。
With home heating systems, people have learned to set the thermostat slightly higher than the actual temperature they are aiming at. Exactly how much higher can be a tricky question, because the outflow rate is higher on cold days than on warm days. But for thermostats this control problem

isn't serious. You can muddle your way to a thermostat setting you can live with.
For other systems with this same structure of competing balancing loops, the fact that the stock goes on changing while you're trying to control it can create real problems. For example, suppose you're trying to maintain a store inventory at a certain level. You can't instantly order new stock to make up an immediately apparent shortfall. If you don't account for the goods that will be sold while you are waiting for the order to come in, your inventory will never be quite high enough. You can be fooled in the same way if you're trying to maintain a cash balance at a certain level, or the level of water in a reservoir, or the concentration of a chemical in a continuously flowing reaction system.
There's an important general principle here, and also one specific to the thermostat structure. First the general one: The information delivered by a feedback loop can only affect future behavior; it can't deliver the information, and so can't have an impact fast enough to correct behavior that drove the current feedback. A person in the system who makes a decision based on the feedback can't change the behavior of the system that drove the current feedback; the decisions he or she makes
will affect only future behavior.
Why is that important? Because it means there will always be delays in responding. It says that a flow can't react instantly to a flow. It can react only to a change in a stock, and only after a slight delay to register the incoming information. In the bathtub, it takes a split second of time to assess the depth of the water and decide to adjust the flows. Many economic models make a mistake in this matter by assuming that consumption or produc-
The information delivered by a feedback loop-even nonphysical feedbackcan only affect future behavior; it can't deliver a signal fast enough to correct behavior that drove the current feedback. Even nonphysical information takes time to feedback into the system. tion can respond immediately, say, to a change in price. That's one of the reasons why real economies tend not to behave exactly like many economic models.
The specific principle you can deduce from this simple system is that you must remember in thermostat-like systems to take into account whatever draining or filling processes are going on. If you don't, you won't achieve the target level of your stock. If you want your room temperature to be at , you have to set the thermostat a little above the desired
从这个简单的系统中可以得出的具体原则是,在类似恒温器的系统中,您必须记住要考虑到正在进行的任何排水或填充过程。否则,就无法达到目标库存水平。如果您希望室温保持在 ,则必须将恒温器设置得比所需温度稍高一些。

temperature. If you want to pay off your credit card (or the national debt), you have to raise your repayment rate high enough to cover the charges you incur while you're paying (including interest). If you're gearing up your work force to a higher level, you have to hire fast enough to correct for
A stock-maintaining balancing feedback loop must have its goal set appropriately to compensate for draining or inflowing processes that affect that stock. Otherwise, the feedback process will fall short of or exceed the target for the stock. those who quit while you are hiring. In other words, your mental model of the system needs to include all the important flows, or you will be surprised by the system's behavior.
Before we leave the thermostat, we should see how it behaves with a varying outside temperature. Figure 19 shows a twenty-four-hour period of normal operation of a well-functioning thermostat system, with the outside temperature dipping well below freezing. The inflow of heat from the furnace nicely tracks the outflow of heat to the outside. The temperature in the room varies hardly at all once the room has warmed up.
在离开恒温器之前,我们应该看看恒温器在室外温度变化时的表现。图 19 显示了一个功能良好的恒温器系统正常运行 24 小时的情况,室外温度降到了零度以下。炉子的热量流入很好地跟踪了热量流出室外的情况。一旦房间暖和起来,室内温度几乎没有变化。
Every balancing feedback loop has its breakdown point, where other loops pull the stock away from its goal more strongly than it can pull back. That can happen in this simulated thermostat system, if I weaken the power of the heating loop (a smaller furnace that cannot put out as much heat), or if I strengthen the power of the cooling loop (colder outside tempera-
Figure 19. The furnace warms a cool room, even as heat leaks from the room and outside temperatures drop below freezing.
图 19.即使房间漏出热量,室外温度降至零度以下,火炉也能为凉爽的房间供暖。

ture, less insulation, or larger leaks). Figure 20 shows what happens with the same outside temperatures as in Figure 19, but with faster heat loss from the room. At very cold temperatures, the furnace just can't keep up with the heat drain. The loop that is trying to bring the room temperature down to the outside temperature dominates the system for a while. The room gets pretty uncomfortable!
图 20 显示了在室外温度与图 19 相同,但室内热量损失较快的情况。)图 20 显示了在室外温度与图 19 相同的情况下,室内热量损失更快的情况。在非常寒冷的温度下,炉子无法跟上热量流失的速度。试图将室温降至室外温度的环路会在一段时间内主导系统。房间会变得非常不舒服!
Figure 20. On a cold day, the furnace can't keep the room warm in this leaky house!
图 20.在寒冷的日子里,这个漏水的房子里的炉子无法保持室内温暖!
See if you can follow, as time unfolds, how the variables in Figure 20 relate to one another. At first, both the room and the outside temperatures are cool. The inflow of heat from the furnace exceeds the leak to the outside, and the room warms up. For an hour or two, the outside is mild enough that the furnace replaces most of the heat that's lost to the outside, and the room temperature stays near the desired temperature.
看看您能否随着时间的推移,了解图 20 中各变量之间的关系。起初,室内和室外的温度都很低。从炉子中流入的热量超过了向室外泄漏的热量,室内温度升高。在一两个小时内,室外温度较低,炉子可以补充大部分向室外散失的热量,室温保持在理想温度附近。
But as the outside temperature falls and the heat leak increases, the furnace cannot replace the heat fast enough. Because the furnace is generating less heat than is leaking out, the room temperature falls. Finally, the outside temperature rises again, the heat leak slows, and the furnace, still operating at full tilt, finally can pull ahead and start to warm the room again.
Just as in the rules for the bathtub, whenever the furnace is putting in more heat than is leaking out, the room temperature rises. Whenever the inflow rate falls behind the outflow rate, the temperature falls. If you

study the system changes on this graph for a while and relate them to the feedback-loop diagram of this system, you'll get a good sense of how the structural interconnections of this system-its two feedback loops and how they shift in strength relative to each other-lead to the unfolding of the system's behavior over time.
A Stock with One Reinforcing Loop and One Balancing Loop-Population and
Industrial Economy 工业经济
What happens when a reinforcing and a balancing loop are both pulling on the same stock? This is one of the most common and important system structures. Among other things, it describes every living population and every economy.
Figure 21. Population governed by a reinforcing loop of births and a balancing loop of deaths.
图 21.人口受出生强化循环和死亡平衡循环的制约。
A population has a reinforcing loop causing it to grow through its birth rate, and a balancing loop causing it to die off through its death rate.
As long as fertility and mortality are constant (which in real systems they rarely are), this system has a simple behavior. It grows exponentially or dies off, depending on whether its reinforcing feedback loop determining births is stronger than its balancing feedback loop determining deaths.
For example, the 2007 world population of 6.6 billion people had a fertility rate of roughly 21 births a year for every 1,000 people in the population. Its mortality rate was 9 deaths a year out of every 1,000 people. Fertility was higher than mortality, so the reinforcing loop dominated the system. If those fertility and mortality rates continue unchanged, a child born
例如,2007 年世界人口为 66 亿,生育率约为每 1 000 人每年出生 21 人。死亡率为每 1000 人中每年有 9 人死亡。生育率高于死亡率,因此强化循环在整个系统中占主导地位。如果生育率和死亡率继续保持不变,那么出生的孩子
Figure 22. Population growth if fertility and mortality maintain their 2007 levels of 21 births and nine deaths per 1,000 people.
图 22.如果生育率和死亡率保持 2007 年每千人 21 例出生和 9 例死亡的水平,人口增长情况。
now will see the world population more than double by the time he or she reaches the age of 60, as shown in Figure 22.
如图 22 所示,到 60 岁时,世界人口将增加一倍多。
If, because of a terrible disease, the mortality rate were higher, say at 30 deaths per 1,000 , while the fertility rate remained at 21 , then the death loop
如果由于某种可怕的疾病,死亡率升高,例如每 1 000 人中有 30 人死亡,而生育率仍为 21,那么死亡圈
Figure 23. Population decline if fertility remains at 2007 level (21 births per 1,000) but mortality is much higher, 30 deaths per 1,000 .
图 23.如果生育率保持在 2007 年的水平(每 1 000 人出生 21 人),但死亡率大幅上升(每 1 000 人死亡 30 人),则人口下降。
would dominate the system. More people would die each year than would be born, and the population would gradually decrease (Figure 23).
将主导整个系统。每年死亡的人将多于出生的人,人口将逐渐减少(图 23)。
Things get more interesting when fertility and mortality change over time. When the United Nations makes long-range population projections, it generally assumes that, as countries become more developed, average fertility will decline (approaching replacement where on average each woman has 1.85 children). Until recently, assumptions about mortality were that it would also decline, but more slowly (because it is already low in most parts of the world). However, because of the epidemic of HIV/ AIDS, the UN now assumes the trend of increasing life expectancy over the next fifty years will slow in regions affected by HIV/AIDS.
当生育率和死亡率随时间发生变化时,情况就变得更加有趣了。联合国在进行长期人口预测时,通常假定随着国家变得越来越发达,平均生育率将下降(接近更替期,即平均每个妇女生育 1.85 个孩子)。直到最近,关于死亡率的假设是,死亡率也会下降,但下降速度较慢(因为世界上大多数地区的死亡率已经很低)。然而,由于艾滋病毒/艾滋病的流行,联合国现在假定,在受艾滋病毒/艾滋病影响的地区,未来五十年预期寿命延长的趋势将放缓。
Changing flows (fertility and mortality) create a change in the behavior over time of the stock (population)—the line bends. If, for example, world fertility falls steadily to equal mortality by the year 2035 and they both stay
流量(生育率和死亡率)的变化会导致存量(人口)的行为随时间发生变化--即线弯曲。例如,如果世界生育率持续下降,到 2035 年与死亡率持平,并且两者都保持
Figure 24. Population stabilizes when fertility equals mortality.
图 24当生育率等于死亡率时,人口趋于稳定。
constant thereafter, the population will level off, births exactly balancing deaths in dynamic equilibrium, as in Figure 24.
此后,人口将趋于稳定,出生人数与死亡人数完全平衡,达到动态平衡,如图 24 所示。
This behavior is an example of shifting dominance of feedback loops. Dominance is an important concept in systems thinking. When one loop dominates another, it has a stronger impact on behavior. Because systems often have several competing feedback loops operating simultaneously, those loops that dominate the system will determine the behavior.
At first, when fertility is higher than mortality, the reinforcing growth loop dominates the system and the resulting behavior is exponential

growth. But that loop is gradually weakened as fertility falls. Finally, it exactly equals the strength of the balancing loop of mortality. At that point neither loop dominates, and we have dynamic equilibrium.
You saw shifting dominance in the thermostat system, when the outside temperature fell and the heat leaking out of the poorly insulated house overwhelmed the ability of the furnace to put heat into the room. Dominance shifted from the heating loop to the cooling loop.
Complex behaviors of systems often arise as the relative strengths of feedback loops shift, causing first one loop and then another to dominate behavior.
There are only a few ways a population system could behave, and these depend on what happens to the "driving" variables, fertility and mortality. These are the only ones possible for a simple system of one reinforcing and one balancing loop. A stock governed by linked reinforcing and balancing loops will grow exponentially if the reinforcing loop dominates the balancing one. It will die off if the balancing loop dominates the reinforcing one. It will level off if the two loops are of equal strength (see Figure 25). Or it will do a sequence of these things, one after another, if the relative strength of the two loops change over time (see Figure 26).
人口系统只有几种表现形式,它们取决于 "驱动 "变量--生育率和死亡率--的变化情况。对于只有一个强化循环和一个平衡循环的简单系统来说,只有这几种可能。如果强化环路支配平衡环路,则受强化环路和平衡环路联动支配的种群将呈指数增长。如果平衡环路在强化环路中占主导地位,股票就会消亡。如果两个循环的强度相当,则会趋于平稳(见图 25)。或者,如果两个环路的相对强度随着时间的推移发生变化,则会出现上述一系列情况(见图 26)。
I chose some provocative population scenarios here to illustrate a point about models and the scenarios they can generate. Whenever you are confronted with a scenario (and you are, every time you hear about an economic prediction, a corporate budget, a weather forecast, future climate change, a stockbroker saying what is going to happen to a particular holding), there are questions you need to ask that will help you decide how good a representation of reality is the underlying model.
  • Are the driving factors likely to unfold this way? (What are birth rate and death rate likely to do?)
  • If they did, would the system react this way? (Do birth and death rates really cause the population stock to behave as we think it will?)
-What is driving the driving factors? (What affects birth rate? What affects death rate?)
-驱动因素是什么?(是什么影响了出生率? 是什么影响了死亡率?)
The first question can't be answered factually. It's a guess about the future, and the future is inherently uncertain. Although you may have a strong
A: Growth 答:增长
B: Decline B: 下降
C: Stabilization C:稳定
Figure 25. Three possible behaviors of a population: growth, decline, and stabilization.
图 25.人口的三种可能行为:增长、下降和稳定。
opinion about it, there's no way to prove you're right until the future actually happens. A systems analysis can test a number of scenarios to see what happens if the driving factors do different things. That's usually one purpose of a systems analysis. But you have to be the judge of which scenario, if any, should be taken seriously as a future that might really be possible.
Figure 26. Shifting dominance of fertility and mortality loops.
图 26.生育率和死亡率循环的主导地位变化。
Dynamic systems studies usually are not designed to predict what will happen. Rather, they're designed to explore what would happen, if a number of driving factors unfold in a range of different ways.
The second question-whether the system really will react this way-is more scientific. It's a question about how good the model is. Does it capture the inherent dynamics of the system? Regardless of whether you think the driving factors will do that, would the system behave like that if they did?
In the population scenarios above, however System dynamics models likely you think they are, the answer to this explore possible futures and ask "what if" questions. second question is roughly yes, the population would behave like this, if the fertility and mortality did that. The population model I have used here is very simple. A more detailed model would distinguish age groups, for example. But basically this model responds the way a real population would, growing under the conditions when a real
在上述人口情景中,无论你认为系统动力学模型有多大的可能性,答案都是探索可能的未来,并提出 "如果 "的问题。第二个问题大致是肯定的,如果生育率和死亡率是这样,人口就会这样。我在这里使用的人口模型非常简单。更详细的模型会区分年龄组等。但基本上,这个模型的反应方式与真实人口的反应方式相同,即在真实人口增长的条件下增长。


  1. Are the driving factors likely to unfold this way?
  2. If they did, would the system react this way?
  3. What is driving the driving factors?
Model utility depends not on whether its driving scenarios are realistic (since no one can know that for sure), but on whether it responds with a realistic pattern of behavior.
population would grow, declining when a real population would decline. The numbers are off, but the basic behavior pattern is realistic.
Finally, there is the third question. What is driving the driving factors? What is adjusting the inflows and outflows? This is a question about system boundaries. It requires a hard look at those driving factors to see if they are actually independent, or if they are also embedded in the
system. 系统
Is there anything about the size of the population, for instance, that might feed back to influence fertility or mortality? Do other factors-economics, the environment, social trends-influence fertility and mortality? Does the size of the population affect those economic and environmental and social factors?
Of course, the answer to all of these questions is yes. Fertility and mortality are governed by feedback loops too. At least some of those feedback loops are themselves affected by the size of the population. This population "animal" is only one piece of a much larger system.
当然,所有这些问题的答案都是肯定的。生育率和死亡率也受反馈回路的制约。至少其中一些反馈回路本身会受到人口规模的影响。人口 "动物 "只是一个更大系统中的一个部分。
One important piece of the larger system that affects population is the economy. At the heart of the economy is another reinforcing-loop-plusbalancing-loop system-the same kind of structure, with the same kinds
Figure 27. Like a living population, economic capital has a reinforcing loop (investment of output) governing growth and a balancing loop (depreciation) governing decline.
图 27.与有生命的人口一样,经济资本也有一个促进增长的循环(产出投资)和一个平衡衰退的循环(折旧)。

of behavior, as the population (see Figure 27).
的行为(见图 27)。
The greater the stock of physical capital (machines and factories) in the economy and the efficiency of production (output per unit of capital), the more output (goods and services) can be produced each year.
The more output that is produced, the more can be invested to make new capital. This is a reinforcing loop, like the birth loop for a population. The investment fraction is equivalent to the fertility. The greater the fraction of its output a society invests, the faster its capital stock will grow.
Physical capital is drained by depreciation-obsolescence and wearingout. The balancing loop controlling depreciation is equivalent to the death loop in a population. The "mortality" of capital is determined by the average capital lifetime. The longer the lifetime, the smaller the fraction of capital that must be retired and replaced each year.
有形资本因折旧--陈旧和磨损而耗尽。控制折旧的平衡循环相当于人口的死亡循环。资本的 "死亡率 "由资本的平均寿命决定。寿命越长,每年必须报废和更换的资本比例就越小。
If this system has the same structure as the population system, it must have the same repertoire of behaviors. Over recent history world capital, like world population, has been dominated by its reinforcing loop and has been growing exponentially. Whether in the future it grows or stays constant or dies off depends on whether its reinforcing growth loop remains stronger than its balancing depreciation loop. That depends on
  • the investment fraction-how much output the society invests rather than consumes,
  • the efficiency of capital—how much capital it takes to produce a given amount of output, and
  • the average capital lifetime.
If a constant fraction of output is reinvested in the capital stock and the efficiency of that capital (its ability to produce output) is also constant, the capital stock may decline, stay constant, or grow, depending on the lifetime of the capital. The lines in Figure 28 show systems with different average capital lifetimes. With a relatively short lifetime, the capital wears out faster than it is replaced. Reinvestment does not keep up with depreciation and the economy slowly declines. When depreciation just balances investment, the economy is in dynamic equilibrium. With a long lifetime, the capital stock grows exponentially. The longer the lifetime of capital, the faster it grows.
如果产出的固定部分再投资于资本存量,并且资本的效率(生产产出的能力)也保持不变,那么资本存量可能会下降、保持不变或增长,这取决于资本的寿命。图 28 中的线条显示了不同平均资本寿命的系统。资本寿命相对较短时,资本的损耗速度快于资本的更新速度。再投资跟不上折旧,经济缓慢衰退。当折旧刚好与投资平衡时,经济处于动态平衡。如果资本寿命长,资本存量就会呈指数增长。资本寿命越长,增长速度越快。
This is another example of a principle we've already encountered: You can make a stock grow by decreasing its outflow rate as well as by increas-
Figure 28. Growth in capital stock with changes in the lifetime of the capital. In a system with output per unit capital ratio of 1:3 and an investment fraction of 20 percent, capital with a lifetime of 15 years just keeps up with depreciation. A shorter lifetime leads to a declining stock of capital.
图 28.资本存量的增长与资本寿命的变化。在单位资本产出比为 1:3、投资比例为 20%的系统中,使用寿命为 15 年的资本刚刚跟上折旧。寿命越短,资本存量越少。
ing its inflow rate!
Just as many factors influence the fertility and mortality of a population, so many factors influence the output ratio, investment fraction, and the lifetime of capital—interest rates, technology, tax policy, consumption habits, and prices, to name just a few. Population itself influences investment, both by contributing labor to output, and by increasing demands on consumption, thereby decreasing the investment fraction. Economic output also feeds back to influence population in many ways. A richer economy usually has better health care and a lower death rate. A richer economy also usually has a lower birth rate.
In fact, just about any long-term model of a real economy should link together the two structures of population and capital to show how they affect each other. The central question of economic development is how to keep the reinforcing loop of capital accumulation from growing more slowly than the reinforcing loop of population growth-so that people are
Systems with similar feedback structures produce similar dynamic behaviors. getting richer instead of poorer.
It may seem strange to you that I call the capital system the same kind of "zoo animal" as the population system. A production system with factories and shipments and economic flows doesn't look much like a population system with babies being born and people aging
我把资本系统称为与人口系统同类的 "动物园动物",你可能会觉得奇怪。有工厂、运输和经济流动的生产系统与有婴儿出生和人口老龄化的人口系统看起来并不太一样。

and having more babies and dying. But from a systems point of view these systems, so dissimilar in many ways, have one important thing in common: their feedback-loop structures. Both have a stock governed by a reinforcing growth loop and a balancing death loop. Both also have an aging process. Steel mills and lathes and turbines get older and die just as people do.
One of the central insights of systems theory, as central as the observation that systems largely cause their own behavior, is that systems with similar feedback structures produce similar dynamic behaviors, even if the outward appearance of these systems is completely dissimilar.
A population is nothing like an industrial economy, except that both can reproduce themselves out of themselves and thus grow exponentially. And both age and die. A coffee cup cooling is like a warmed room cooling, and like a radioactive substance decaying, and like a population or industrial economy aging and dying. Each declines as the result of a balancing feedback loop.

A System with Delays-Business Inventory

Picture a stock of inventory in a store-a car dealership—with an inflow of deliveries from factories and an outflow of new car sales. By itself, this stock of cars on the dealership lot would behave like the water in a bathtub.
Figure 29. Inventory at a car dealership is kept steady by two competing balancing loops, one through sales and one through deliveries.
图 29.汽车经销商的库存是通过两个相互竞争的平衡循环来保持稳定的,一个是销售,另一个是交付。
Now picture a regulatory feedback system designed to keep the inventory high enough so that it can always cover ten days' worth of sales (see Figure 29). The car dealer needs to keep some inventory because deliveries and purchases don't match perfectly every day. Customers make purchases that are unpredictable on a day-to-day basis. The car dealer also needs to provide herself with some extra inventory (a buffer) in case deliveries from suppliers are delayed occasionally.
现在设想一个监管反馈系统,其目的是保持足够高的库存,使其总能满足十天的销售量(见图 29)。汽车经销商需要保持一定的库存,因为每天的交货量和购买量并不完全匹配。客户每天的购买量是不可预测的。汽车经销商还需要为自己准备一些额外的库存(缓冲),以防供应商偶尔延迟交货。
The dealer monitors sales (perceived sales), and if, for example, they seem to be rising, she adjusts orders to the factory to bring inventory up to her new desired inventory that provides ten days' coverage at the higher sales rate. So, higher sales mean higher perceived sales, which means a higher discrepancy between inventory and desired inventory, which means higher orders, which will bring in more deliveries, which will raise inventory so it can comfortably supply the higher rate of sales.
This system is a version of the thermostat system-one balancing loop of sales draining the inventory stock and a competing balancing loop maintaining the inventory by resupplying what is lost in sales. Figure 30 shows the not very surprising result of an increase in consumer demand of 10 percent.
该系统是恒温器系统的一个版本--销售平衡循环消耗库存存货,竞争平衡循环通过补充销售损失的存货来维持库存。图 30 显示了消费者需求增加 10% 后并不令人惊讶的结果。
In Figure 31, I am putting something else into this simple model—three delays that are typical of what we experience in the real world.
在图 31 中,我在这个简单的模型中加入了其他东西--我们在现实世界中经历的典型的三种延迟。
First, there is a perception delay, intentional in this case. The car dealer doesn't react to just any blip in sales. Before she makes ordering decisions,
Figure 30. Inventory on the car dealership's lot with a permanent 10 -percent increase in consumer demand starting on day 25 .
图 30.在消费者需求从第 25 天开始持续增长 10%的情况下,汽车经销商的库存情况。
Figure 31. Inventory at a car dealership with three common delays now included in the picture-a perception delay, a response delay, and a delivery delay.
图 31.汽车经销商的库存,图片中包括三种常见延迟--感知延迟、响应延迟和交付延迟。
she averages sales over the past five days to sort out real trends from temporary dips and spikes.
Second, there is a response delay. Even when it's clear that orders need to be adjusted, she doesn't try to make up the whole adjustment in a single order. Rather, she makes up one-third of any shortfall with each order. Another way of saying that is, she makes partial adjustments over three days to be extra sure the trend is real. Third, there is a delivery delay. It takes five days for the supplier at the factory to receive an order, process it, and
Figure 32. Response of inventory to a 10 -percent increase in sales when there are delays in the system.
图 32.当系统出现延迟时,库存对销售额增长 10%的反应。

deliver it to the dealership.
Although this system still consists of just two balancing loops, like the simplified thermostat system, it doesn't behave like the thermostat system. Look at what happens, for example, as shown in Figure 32, when the business experiences the same permanent 10 -percent jump in sales from an increase in customer demand.
虽然这个系统仍然像简化的恒温器系统一样,只由两个平衡回路组成,但它的行为却与恒温器系统不同。例如,如图 32 所示,当企业的销售额因客户需求增加而永久性地增长 10%时,会发生什么情况?
Oscillations! A single step up in sales causes inventory to drop. The car dealer watches long enough to be sure the higher sales rate is going to last. Then she begins to order more cars to both cover the new rate of sales and bring the inventory up. But it takes time for the orders to come in. During that time inventory drops further, so orders have to go up a little more, to bring inventory back up to ten days' coverage.
Eventually, the larger volume of orders starts arriving, and inventory recovers-and more than recovers, because during the time of uncertainty about the actual trend, the owner has ordered too much. She now sees her mistake, and cuts back, but there are still high past orders coming in, so she orders even less. In fact, almost inevitably, since she still can't be sure of what is going to happen next, she orders too little. Inventory gets too low again. And so forth, through a series of oscillations around the new desired inventory level. As Figure 33 illustrates, what a difference a few delays make!
最终,大量订单开始到达,库存恢复了,而且恢复得还不止,因为在不确定实际趋势的那段时间里,店主订购了太多的订单。她现在认识到了自己的错误,于是减少了订货量,但过去的订单量仍然很大,所以她的订货量就更少了。事实上,几乎不可避免的是,由于她仍然无法确定下一步会发生什么,她的订单就会太少。库存再次变得过低。如此往复,围绕新的理想库存水平进行一系列震荡。如图 33 所示,几次延迟带来的影响是多么巨大!
We'll see in a moment that there are ways to damp these oscillations in inventory, but first it's important to understand why they occur. It isn't because the car dealer is stupid. It's because she is struggling to operate
A delay in a balancing feedback loop makes a system likely to oscillate. in a system in which she doesn't have, and can't have, timely information and in which physical delays prevent her actions from having an immediate effect on inventory. She doesn't know what her customers will do next. When they do something, she's not sure they'll keep doing it. When she issues an order, she doesn't see an immediate response. This situation of information insufficiency and physical delays is very common. Oscillations like these are frequently encountered in inventories and in many other systems. Try taking a shower sometime where there's a very long pipe between the hot- and cold-water mixer and the showerhead, and you'll experience directly the joys of hot and cold oscillations because of a long response delay.
How much of a delay causes what kind of oscillation under what circum-

Figure 33. The response of orders and deliveries to an increase in demand. shows the small but sharp step up in sales on day 25 and the car dealer's "perceived" sales, in which she averages the change over 3 days. shows the resulting ordering pattern, tracked by the actual deliveries from the factory.
图 33:订单和交货对需求增长的反应。 显示了第 25 天小幅但急剧上升的销售额,以及汽车经销商 "感知到的 "销售额,即她对 3 天变化的平均值。 显示了由此产生的订货模式,由工厂的实际交货量跟踪。
stances is not a simple matter. I can use this inventory system to show you why.
"These oscillations are intolerable," says the car dealer (who is herself a learning system, determined now to change the behavior of the inventory system). "'I'm going to shorten the delays. There's not much I can do about the delivery delay from the factory, so I'm going to react faster myself. I'll average sales trends over only two days instead of five before I make order adjustments."
Figure 34 illustrates what happens when the dealer's perception delay is
图 34 说明了当经销商的感知延迟为

shortened from five days to two.
Not much happens when the car dealer shortens her perception delay. If anything the oscillations in the inventory of cars on the lot are a bit worse. And if, instead of shortening her perception time, the car dealer tries shortening her reaction time-making up perceived shortfalls in two days instead of three-things get very much worse, as shown in Figure 35. Something has to change and, since this system has a learning person
当汽车经销商缩短其感知延迟时,并不会发生什么。如果说有什么变化的话,那就是停车场上汽车存量的波动变得更严重了。如果汽车经销商不缩短她的感知时间,而是尝试缩短她的反应时间,将感知到的短缺时间从三天缩短到两天,情况就会变得更糟,如图 35 所示。必须有所改变,因为这个系统有一个学习者
Figure 34. The response of inventory to the same increase in demand with a shortened perception delay.
图 34.在感知延迟缩短的情况下,库存对相同需求增长的反应。
Figure 35. The response of inventory to the same increase in demand with a shortened reaction time. Acting faster makes the oscillations worse!
图 35.反应时间缩短后,库存对相同需求增长的反应。行动越快,振荡越严重!

within it, something will change. "High leverage, wrong direction," the system-thinking car dealer says to herself as she watches this failure of a policy intended to stabilize the oscillations. This perverse kind of result can be seen all the time-someone trying to fix a system is attracted intuitively to a policy lever that in fact does have a strong effect on the system. And then the well-intentioned fixer pulls the lever in the wrong direction! This is just one example of how we can be surprised by the counterintuitive behavior of systems when we start trying to change them.
Part of the problem here is that the car dealer has been reacting not too slowly, but too quickly. Given the configuration of this system, she has been overreacting. Things would go better if, instead of decreasing her response delay from three days to two, she would increase the delay from three days to six, as illustrated in Figure 36.
这里的部分问题是,汽车经销商的反应不是太慢,而是太快。从这个系统的配置来看,她反应过度了。如果她不把反应延迟从三天缩短到两天,而是把延迟从三天延长到六天,情况就会好一些,如图 36 所示。
As Figure 36 shows, the oscillations are greatly damped with this change, and the system finds its new equilibrium fairly efficiently.
如图 36 所示,这种变化极大地抑制了振荡,系统相当有效地找到了新的平衡。
The most important delay in this system is the one that is not under the direct control of the car dealer. It's the delay in delivery from the Delays are pervasive in systems, factory. But even without the ability to change and they are strong determinants of behavior. Changing the length of a delay may (or may not, depending on the type of delay and the relative lengths of other delays) make a large change in the behavior of a system. that part of her system, the dealer can learn to manage inventory quite well.
Figure 36. The response of inventory to the same increase in demand with a slowed reaction time.
图 36.反应时间减慢后,库存对相同需求增长的反应。
Changing the delays in a system can make it much easier or much harder to manage. You can see why system thinkers are somewhat fanatic on the subject of delays. We're always on the alert to see where delays occur in systems, how long they are, whether they are delays in information streams or in physical processes. We can't begin to understand the dynamic behavior of systems unless we know where and how long the delays are. And we are aware that some delays can be powerful policy levers. Lengthening or shortening them can produce major changes in the behavior of systems.
In the big picture, one store's inventory problem may seem trivial and fixable. But imagine that the inventory is that of all the unsold automobiles in America. Orders for more or fewer cars affect production not only at assembly plants and parts factories, but also at steel mills, rubber and glass plants, textile producers, and energy producers. Everywhere in this system are perception delays, production delays, delivery delays, and construction delays. Now consider the link between car production and jobs-increased production increases the number of jobs allowing more people to buy cars. That's a reinforcing loop, which also works in the opposite directionless production, fewer jobs, fewer car sales, less production. Put in another reinforcing loop, as speculators buy and sell shares in the auto and autosupply companies based on their recent performance, so that an upsurge in production produces an upsurge in stock price, and vice versa.
That very large system, with interconnected industries responding to each other through delays, entraining each other in their oscillations, and being amplified by multipliers and speculators, is the primary cause of business cycles. Those cycles don't come from presidents, although presidents can do much to ease or intensify the optimism of the upturns and the pain of the downturns. Economies are extremely complex systems; they are full of balancing feedback loops with delays, and they are inherently oscillatory.

Two-Stock Systems 双库存系统

A Renewable Stock Constrained by a Nonrenewable Stock-an Oil Economy The systems I've displayed so far have been free of constraints imposed by their surroundings. The capital stock of the industrial economy model didn't require raw materials to produce output. The population didn't need food. The thermostat-furnace system never ran out of oil. These simple
可再生存量受制于不可再生存量--石油经济 到目前为止,我所展示的系统都没有受到周围环境的限制。工业经济模型的资本存量不需要原材料来生产产出。人口不需要食物。恒温器-火炉系统永远不会耗尽石油。这些简单的

models of the systems have been able to operate according to their unconstrained internal dynamics, so we could see what those dynamics are.
But any real physical entity is always surrounded by and exchanging things with its environment. A corporation needs a constant supply of energy and materials and workers and managers and customers. A growing corn crop needs water and nutrients and protection from pests. A population needs food and water and living space, and if it's a human population, it needs jobs and education and health care and a multitude of other things. Any entity that is using energy and processing materials needs a place to put its wastes, or a process to carry its wastes away.
Therefore, any physical, growing system is going to run into some kind of constraint, sooner or later. That constraint will take the form of a balancing loop that in some way shifts the dominance of the reinforcing loop driving the growth behavior, either by strengthening the outflow or by weakening the inflow.
Growth in a constrained environment is very common, so common that systems thinkers call it the "limits-to-growth" archetype. (We'll explore more archetypes-frequently found system structures that produce familiar behavior patterns-in Chapter Five.) Whenever we see a growing entity, whether it be a population, a corporation, a bank account, a rumor, an epidemic, or sales of a new product, we look for the reinforcing loops that are driving it and for the balancing loops that ultimately will constrain it. We know those balancing loops are there, even if they are not yet dominating the system's behavior, because no real physical system can grow forever. Even a hot new product will saturate the market eventually. A chain reaction in a nuclear power plant or bomb will run out of fuel. A virus will run out of susceptible people to infect. An economy may be constrained by physical In physical, exponentially capital or monetary capital or labor or markets or growing systems, there must be at least one reinforcing loop driving the growth and at least one balancing loop constraining the growth, because no physical system can grow forever in a finite environment. management or resources or pollution.
在受限环境中成长是非常常见的现象,以至于系统思想家称之为 "成长极限 "原型。(我们将在第五章探讨更多原型--经常发现的产生熟悉行为模式的系统结构)。每当我们看到一个不断增长的实体,无论是人口、公司、银行账户、谣言、流行病,还是新产品的销售,我们都会寻找推动其增长的强化循环,以及最终会限制其增长的平衡循环。我们知道这些平衡回路是存在的,即使它们还没有主导系统的行为,因为没有一个真实的物理系统可以永远发展下去。即使是热门的新产品,最终也会使市场饱和。核电站或炸弹的连锁反应也会耗尽燃料。病毒也会耗尽可感染的易感人群。在物理的、指数式增长的资本、货币资本、劳动力、市场或增长系统中,必须至少有一个强化环路推动增长,至少有一个平衡环路限制增长,因为没有一个物理系统可以在有限的环境中永远增长。
Like resources that supply the inflows to a stock, a pollution constraint can be renewable or nonrenewable. It's nonrenewable if the environment has no capacity to absorb the pollutant or make it harmless. It's renewable if the environment has a finite, usually variable, capacity for removal. Everything said here about resource-constrained systems, therefore,

applies with the same dynamics but opposite flow directions to pollutionconstrained systems.
The limits on a growing system may be temporary or permanent. The system may find ways to get around them for a short while or a long while, but eventually there must come some kind of accommodation, the system adjusting to the constraint, or the constraint to the system, or both to each other. In that accommodation come some interesting dynamics.
Whether the constraining balancing loops originate from a renewable or nonrenewable resource makes some difference, not in whether growth can continue forever, but in how growth is likely to end.
Let's look, to start, at a capital system that makes its money by extracting a nonrenewable resource-say an oil company that has just discovered a huge new oil field. See Figure 37.
首先,让我们来看看一个通过开采不可再生资源来赚钱的资本系统--比如一家刚刚发现了一个巨大新油田的石油公司。见图 37。
The diagram in Figure 37 may look complicated, but it's no more than
图 37 中的图表看似复杂,其实不过是
Figure 37. Economic capital, with its reinforcing growth loop constrained by a nonrenewable resource.
图 37.经济资本,其增长循环受制于不可再生资源。

a capital-growth system like the one we've already seen, using "profit" instead of "output." Driving depreciation is the now-familiar balancing loop: the more capital stock, the more machines and refineries there are that fall apart and wear out, reducing the stock of capital. In this example, the capital stock of oil drilling and refining equipment depreciates with a 20 -year lifetime-meaning (or 5 percent) of the stock is taken out of commission each year. It builds itself up through investment of profits from oil extraction. So we see the reinforcing loop: More capital allows more resource extraction, creating more profits that can be reinvested. I've assumed that the company has a goal of 5 percent annual growth in its business capital. If there isn't enough profit for 5 percent growth, the company invests whatever profits it can.
这种资本增长体系就像我们已经看到过的,用 "利润 "代替 "产出"。推动折旧的是我们现在熟悉的平衡循环:资本存量越多,就有越多的机器和炼油厂发生故障和磨损,从而减少资本存量。在这个例子中,石油钻探和提炼设备的资本存量折旧年限为 20 年,这意味着 (或 5%)的存量每年都会停止使用。它通过投资石油开采的利润自我积累。因此,我们看到了一个不断强化的循环:更多的资本可以开采更多的资源,从而创造更多的利润用于再投资。我假定该公司的目标是业务资本每年增长 5%。如果没有足够的利润来实现 5% 的增长,公司就会将所有利润用于投资。
Profit is income minus cost. Income in this simple representation is just the price of oil times the amount of oil the company extracts. Cost is equal to capital times the operating cost (energy, labor, materials, etc.) per unit of capital. For the moment, I'll make the simplifying assumptions that both price and operating cost per unit of capital are constant.
What is not assumed to be constant is the yield of resource per unit of capital. Because this resource is not renewable, as in the case of oil, the stock feeding the extraction flow does not have an input. As the resource is extracted—as an oil well is depleted-the next barrel of oil becomes harder to get. The remaining resource is deeper down, or more dilute, or in the case of oil, under less natural pressure to force it to the surface. More and more costly and technically sophisticated measures are required to keep the resource coming.
Here is a new balancing feedback loop that ultimately will control the growth of capital: the more capital, the higher the extraction rate. The higher the extraction rate, the lower the resource stock. The lower the resource stock, the lower the yield of resource per unit of capital, so the lower the profit (with price assumed constant) and the lower the investment rate-therefore, the lower the rate of growth of capital. I could assume that resource depletion feeds back through operating cost as well as capital efficiency. In the real world it does both. In either case, the ensuing behavior pattern is the same-the classic dynamics of depletion (see Figure 38).
这里有一个新的平衡反馈回路,它最终将控制资本的增长:资本越多,开采率越高。开采率越高,资源存量越低。资源存量越低,每单位资本的资源产量就越低,因此利润就越低(假设价格不变),投资率就越低--因此,资本增长率就越低。我可以假设,资源损耗会通过运营成本和资本效率反馈回来。在现实世界中,两者都会产生影响。无论哪种情况,随之而来的行为模式都是一样的--典型的耗竭动态(见图 38)。
The system starts out with enough oil in the underground deposit to supply the initial scale of operation for 200 years. But, actual extraction peaks at about 40 years because of the surprising effect of exponential
系统开始时,地下储藏的石油足以满足最初 200 年的开采规模。但是,由于令人惊讶的指数效应,实际开采量在 40 年左右达到峰值。
A: Extraction rate A:提取率
B: Capital stock B: 资本存量
C: Resource stock C:资源存量
Figure 38. Extraction (A) creates profits that allow for growth of capital (B) while depleting the nonrenewable resource (C). The greater the accumulation of capital, the faster the resource is depleted.
图 38.开采(A)创造利润,使资本(B)增长,同时耗尽不可再生资源(C)。资本积累越多,资源消耗得越快。
growth in extraction. At an investment rate of 10 percent per year, the capital stock and therefore the extraction rate both grow at 5 percent per year and so double in the first 14 years. After 28 years, while the capital stock has quadrupled, extraction is starting to lag because of falling yield per unit of capital. By year 50 the cost of maintaining the capital stock has overwhelmed the income from resource extraction, so profits are no longer sufficient to keep investment ahead of depreciation. The operation quickly shuts down, as the capital stock declines. The last and most expensive of the resource stays in the ground; it doesn't pay to get it out.
开采增长。在每年 10%的投资率下,资本存量和开采率都以每年 5%的速度增长,因此在最初的 14 年中翻了一番。28 年后,虽然资本存量翻了两番,但由于单位资本产量下降,开采开始滞后。到第 50 年,维持资本存量的成本已经超过了资源开采的收入,因此利润已经不足以使投资超过折旧。随着资本存量的下降,企业很快就关闭了。最后也是最昂贵的资源留在了地下;开采出来也没有任何回报。
What happens if the original resource turns out to be twice as large as

the geologists first thought-or four times as large? Of course, that makes a huge difference in the total amount of oil that can be extracted from this field. But with the continued goal of 10 percent per year reinvestment producing 5 percent per year capital growth, each doubling of the resource makes a difference of only about 14 years in the timing of the peak extraction rate, and in the lifetime of any jobs or
还是四倍之大?当然,这对该油田可开采的石油总量影响巨大。但是,如果继续以每年 10% 的再投资和每年 5% 的资本增长为目标,资源量每增加一倍,在开采量达到峰值的时间上,以及在任何工作或工作岗位的寿命上,都只会相差 14 年左右。
A quantity growing exponentially toward a constraint or limit reaches that limit in a surprisingly short time. communities dependent on the extraction industry (see Figure 39).
一个数量向一个限制或极限呈指数增长,在很短的时间内就会达到极限,依赖开采业的社区就是如此(见图 39)。
The higher and faster you grow, the farther and faster you fall, when you're building up a capital stock dependent on a nonrenewable resource. In the face of exponential growth of extraction or use, a doubling or quadrupling of the nonrenewable resource give little added time to develop alternatives.
If your concern is to extract the resource and make money at the maximum possible rate, then the ultimate size of the resource is the most important number in this system. If, say, you're a worker at the mine or oil field, and your concern is with the lifetime of your job and stability of your community, then there are two important numbers: the size of the resource and the desired growth rate of capital. (Here is a good example of the goal of a feedback loop being crucial to the behavior of a system.) The real choice in the management of a nonrenewable resource is whether to get rich very fast or to get less rich but stay that way longer.
Figure 39. Extraction with two times or four times as large a resource to draw on. Each doubling of the resource makes a difference of only about fourteen years in the peak of extraction.
图 39.资源量增加两倍或四倍后的开采情况。资源量每增加一倍,开采高峰期仅相差约 14 年。
Figure 40. The peak of extraction comes much more quickly as the fraction of profits reinvested increases.
图 40.随着利润再投资比例的增加,榨取峰值来得更快。
The graph in Figure 40 shows the development of the extraction rate over time, given desired growth rates above depreciation varying from 1 percent annually, to 3 percent, 5 percent, and 7 percent. With a 7 percent growth rate, extraction of this "200-year supply" peaks within 40 years. Imagine the effects of this choice not only on the profits of the company, but on the social and natural environments of the region.
图 40 中的图表显示了开采率随时间的变化情况,在预期增长率高于折旧率的情况下,年增长率从 1%到 3%、5% 和 7%不等。如果增长率为 7%,"200 年供应量 "的开采量将在 40 年内达到峰值。试想一下,这种选择不仅会对公司的利润产生影响,还会对该地区的社会和自然环境产生影响。
Earlier I said I would make the simplifying assumption that price was constant. But what if that's not true? Suppose that in the short term the resource is so vital to consumers that a higher price won't decrease demand. In that case, as the resource gets scarce and price rises steeply, as shown in Figure 41.
前面我说过,我会做一个简化假设,即价格是不变的。但如果事实并非如此呢?假设在短期内,资源对消费者非常重要,价格上涨不会减少需求。在这种情况下,随着资源变得稀缺,价格急剧上升,如图 41 所示。
The higher price gives the industry higher profits, so investment goes up, capital stock continues rising, and the more costly remaining resources can be extracted. If you compare Figure 41 with Figure 38, where price was held constant, you can see that the main effect of rising price is to build the capital stock higher before it collapses.
价格上涨给该行业带来了更高的利润,因此投资增加,资本存量继续上升,可以开采成本更高的剩余资源。如果将图 41 与价格保持不变的图 38 进行比较,就会发现价格上涨的主要影响是在资本存量崩溃之前将其提高。
The same behavior results, by the way, if prices don't go up but if technology brings operating costs down-as has actually happened, for example, with advanced recovery techniques from oil wells, with the beneficiation process to extract low-grade taconite from exhausted iron mines, and with the cyanide leaching process that allows profitable extraction even from the tailings of gold and silver mines.
A: Extraction rate A:提取率
B: Capital stock B: 资本存量
C: Resource stock C:资源存量
Figure 41. As price goes up with increasing scarcity, there is more profit to reinvest, and the capital stock can grow larger (B) driving extraction up for longer (A). The consequence is that the resource is depleted even faster at the end.
图 41.由于价格随着稀缺程度的增加而上升,因此有更多的利润可用于再投资,资本存量也会增加(B),从而使开采时间延长(A)。其结果是,资源 ,最后消耗得更快。
We all know that individual mines and fossil fuel deposits and groundwater aquifers can be depleted. There are abandoned mining towns and oil fields all over the world to testify to the reality of the behavior we've seen here. Resource companies understand this dynamic too. Well before depletion makes capital less efficient in one place, companies shift investment to discovery and development of another deposit somewhere else. But, if there are local limits, eventually will there be global ones?
I'll leave you to have this argument with yourself, or with someone of the

opposite persuasion. I will just point out that, according to the dynamics of depletion, the larger the stock of initial resources, the more new discoveries, the longer the growth loops elude the control loops, and the higher the capital stock and its extraction rate grow, and the earlier, faster, and farther will be the economic fall on the back side of the production peak.
Unless, perhaps, the economy can learn to operate entirely from renewable resources.

Renewable Stock Constrained by a Renewable Stock-a Fishing Economy

Assume the same capital system as before, except that now there is an inflow to the resource stock, making it renewable. The renewable resource in this system could be fish and the capital stock could be fishing boats. It also could be trees and sawmills, or pasture and cows. Living renewable resources such as fish or trees or grass can regenerate themselves from themselves with a reinforcing feedback loop. Nonliving renewable resources such as sunlight or wind or water in a river are regenerated not through a reinforcing loop, but through a steady input that keeps refilling the resource stock no matter what the current state of that stock might be. This same "renewable resource system" structure occurs in an epidemic of a cold virus. It spares its victims who are then able to catch another cold. Sales of a product people need to buy regularly is also a renewable resource system; the stock of potential customers is ever regenerated. Likewise an insect infestation that destroys part but not all of a plant; the plant can regenerate and the insect can eat more. In all these cases, there is an input that keeps refilling the constraining resource stock (as shown in Figure 42).
We will use the example of a fishery. Once again, assume that the lifetime of capital is 20 years and the industry will grow, if it can, at 5 percent per year. As with the nonrenewable resource, assume that as the resource gets scarce it costs more, in terms of capital, to harvest it. Bigger fishing boats that can go longer distances and are equipped with sonar are needed to find the last schools of fish. Or miles-long drift nets are needed to catch them. Or on-board refrigeration systems are needed to bring them back to port from longer distances. All this takes more capital.
我们以渔业为例。再次假设资本的寿命为 20 年,如果可以的话,该行业将以每年 5%的速度增长。与不可再生资源一样,假设随着资源的稀缺,捕捞的资本成本也会增加。要想找到最后的鱼群,就需要更大的渔船、更远的航程和声纳设备。或者需要数英里长的流网来捕捞。或者需要船载制冷系统,以便从更远的地方将鱼运回港口。所有这些都需要更多的资金。
The regeneration rate of the fish is not constant, but is dependent on the number of fish in the area-fish density. If the fish are very dense, their reproduction rate is near zero, limited by available food and habitat. If the fish population falls a bit, it can regenerate at a faster and faster rate,
Figure 42. Economic capital with its reinforcing growth loop constrained by a renewable resource.
图 42.受可再生资源制约的经济资本及其强化增长循环。
because it can take advantage of unused nutrients or space in the ecosystem. But at some point the fish reproduction rate reaches its maximum. If the population is further depleted, it breeds not faster and faster, but slower and slower. That's because the fish can't find each other, or because another species has moved into its niche.
This simplified model of a fishery economy is affected by three nonlinear relationships: price (scarcer fish are more expensive); regeneration rate (scarcer fish don't breed much, nor do crowded fish); and yield per unit of capital (efficiency of the fishing technology and practices).
This system can produce many different sets of behaviors. Figure 43 shows one of them.
这个系统可以产生许多不同的行为。图 43 展示了其中一种。
In Figure 43, we see capital and fish harvest rise exponentially at first.
在图 43 中,我们可以看到资本和渔获量起初呈指数增长。
The fish population (the resource stock) falls, but that stimulates the fish reproduction rate. For decades the resource can go on supplying an exponentially increasing harvest rate. Eventually, the harvest rises too far and the fish population falls low enough to reduce the profitability of the fishing fleet. The balancing feedback of falling harvest reducing profits brings
B: Capital stock B: 资本存量

C: Resource stock C:资源存量

Figure 43. Annual harvest creates profits that allow for growth of capital stock (B), but the harvest levels off, after a small overshoot in this case. The result of leveling harvest is that the resource stock (C) also stabilizes.
图 43.年收获量 创造的利润使资本存量(B)得以增长,但收获量在小幅超调后趋于平稳。收成持平的结果是资源存量(C)也趋于稳定。

down the investment rate quickly enough to bring the fishing fleet into equilibrium with the fish resource. The fleet can't grow forever, but it can maintain a high and steady harvest rate forever.
Just a minor change in the strength of the controlling balancing feedback loop through yield per unit of capital, however, can make a surpris-

B: Capital stock B: 资本存量

C: Resource stock C:资源存量

Figure 44. A slight increase in yield per unit of capital-increasingly efficient technology in this case-creates a pattern of overshoot and oscillation around a stable value in the harvest rate , the stock of economic capital (B), and in the resource stock.
图 44.单位资本产量的轻微增加--在这种情况下,技术效率不断提高--会在收获率 、经济资本存量(B)和资源存量的稳定值附近产生超调和振荡模式。
A: Harvest rate A: 收获率
B: Capital stock B: 资本存量
C: Resource stock C:资源存量
Figure 45. An even greater increase in yield per unit of capital creates a patterns of overshoot and collapse in the harvest (A), the economic capital (B), and the resource (C).
图 45.每单位资本产量的更大增长会导致收成(A)、经济资本(B)和资源(C)的超调和崩溃。
ing difference. Suppose that in an attempt to raise the catch in the fishery, the industry comes up with a technology to improve the efficiency of the boats (sonar, for example, to find the scarcer fish). As the fish population declines, the fleet's ability to pull in the same catch per boat is maintained just a little longer (see Figure 44).
这就是区别。假设为了提高渔获量,该行业想出了一种提高渔船效率的技术(例如声纳,用来寻找稀少的鱼)。随着鱼群数量的减少,船队每艘船的渔获量保持不变的时间会更长一些(见图 44)。
Figure 44 shows another case of high leverage, wrong direction! This
图 44 显示了另一个高杠杆、方向错误的案例!这

technical change, which increases the productivity of all fishermen, throws the system into instability. Oscillations appear!
If the fishing technology gets even better, the boats can go on operating economically even at very low fish densities. The result can be a nearly complete wipeout both of the fish and of the fishing industry. The consequence is the marine equivalent of desertification. The fish have been turned, for all practical purposes, into a nonrenewable resource. Figure 45 illustrates this scenario.
如果捕鱼技术更上一层楼,即使在鱼群密度很低的情况下,渔船也能继续经济地作业。结果可能是鱼类和捕鱼业几乎全军覆没。其后果相当于海洋沙漠化。实际上,鱼类已经变成了不可再生资源。图 45 展示了这种情况。
In many real economies based on real renewable resources-as opposed to this simple model-the very small surviving population retains the potential to build its numbers back up again, once the capital driving the harvest is gone. The whole pattern is repeated, decades later. Very long-term renewable-resource cycles like these have been observed, for example, in the logging industry in New England, now in its third cycle of growth, overcutting, collapse, and eventual regeneration of the resource. But this is not true for all resource populations. More and more, increases in technology and harvest efficiency have the ability to drive resource populations to extinction.
Whether a real renewable resource system can survive overharvest depends on what happens to it during the time when the resource is severely depleted. A very small fish population may become especially vulnerable to pollution or storms or lack of genetic diversity. If this is a forest or grassland resource, the exposed soils may be vulnerable to erosion. Or the nearly empty ecological niche may be filled in by a competitor. Or perhaps the depleted resource can survive and rebuild itself again.
I've shown three sets of possible behaviors of this renewable resource system here:
  • overshoot and adjustment to a sustainable equilibrium,
  • overshoot beyond that equilibrium followed by oscillation around it, and
  • overshoot followed by collapse of the resource and the industry dependent on the resource.
Which outcome actually occurs depends on two things. The first is the critical threshold beyond which the resource population's ability to regenerate itself is damaged. The second is the rapidity and effectiveness of the balancing feedback loop that slows capital growth as the resource becomes depleted. If the feedback is fast enough to stop capital growth before the critical threshold is reached, the whole system comes smoothly into equilibrium. If the balancing feedback is slower and less effective, the system oscillates. If the balancing loop is very weak, so that capital can go on growing even as the resource is reduced below its threshold ability to regenerate itself, the resource and the industry both collapse.
Neither renewable nor nonrenewable limits to growth allow a physical stock to grow forever, but the constraints they impose are dynamically quite different. The difference comes because of the difference between stocks and flows.
The trick, as with all the behavioral possibilities of complex systems, is to recognize what structures contain which latent behaviors, and what conditions release those behaviors-and, where possible, to arrange the structures and conditions to reduce the probability of destructive behaviors and to encourage the possibility of beneficial ones.
Systems and Us 系统与我们

Why Systems Work So Well

If the land mechanism as a whole is good, then every part is good, whether we understand it or not. If the biota, in the course of aeons, has built something we like but do not understand, then who but a fool would discard seemingly useless parts? To keep every cog and wheel is the first precaution of intelligent tinkering.
—Aldo Leopold, forester
-奥尔多-利奥波德, 林务员
Chapter Two introduced simple systems that create their own behavior based on their structures. Some are quite elegant-surviving the buffeting of the world—and, within limits, regaining their composure and proceeding on about their business of maintaining a room's temperature, depleting an oil field, or bringing into balance the size of a fishing fleet with the productivity of a fishery resource.
If pushed too far, systems may well fall apart or exhibit heretofore unobserved behavior. But, by and large, they manage quite well. And that is the beauty of systems: They can work so well. When systems work well, we see a kind of harmony in their functioning. Think of a community kicking in to high gear to respond to a storm. People work long hours to help victims, talents and skills emerge; once the emergency is over, life goes back to "normal."
如果逼得太紧,系统很可能会崩溃,或者表现出前所未见的行为。但总的来说,它们都能处理得很好。这就是系统的魅力所在:它们可以运行得如此之好。当系统运行良好时,我们会看到其运作中的一种和谐。想一想社区为应对暴风雨而全力以赴的情景。人们长时间工作以帮助灾民,人才和技能不断涌现;一旦紧急情况结束,生活就会恢复 "正常"。
Why do systems work so well? Consider the properties of highly functional systems-machines or human communities or ecosystems-which are familiar to you. Chances are good that you may have observed one of three characteristics: resilience, self-organization, or hierarchy.

Resilience 复原力

Placing a system in a straitjacket of constancy can cause fragility to evolve.
C. S. Holling, 2 ecologist
C.S. 霍林,2 位生态学家
Resilience has many definitions, depending on the branch of engineering, ecology, or system science doing the defining. For our purposes, the normal dictionary meaning will do: "the ability to bounce or spring back into shape, position, etc., after being pressed or stretched. Elasticity. The ability to recover strength, spirits, good humor, or any other aspect quickly." Resilience is a measure of a system's ability to survive and persist within a variable environment. The opposite of resilience is brittleness or rigidity.
Resilience arises from a rich structure of many feedback loops that can work in different ways to restore a system even after a large perturbation. A single balancing loop brings a system stock back to its desired state. Resilience is provided by several such loops, operating through different mechanisms, at different time scales, and with redundancy—one kicking in if another one fails.
A set of feedback loops that can restore or rebuild feedback loops is resilience at a still higher level—meta-resilience, if you will. Even higher metameta-resilience comes from feedback loops that can learn, create, design, and evolve ever more complex restorative structures. Systems that can do this are self-organizing, which will be the next surprising system characteristic I come to.
The human body is an astonishing example of a resilient system. It can fend off thousands of different kinds of invaders, it can tolerate wide ranges of temperature and wide variations in food supply, it can reallocate blood supply, repair rips, gear up or slow down metabo-
There are always limits to resilience. lism, and compensate to some extent for missing or defective parts. Add to it a self-organizing intelligence that can learn, socialize, design technologies, and even transplant body parts, and you have a formidably resilient system-although not infinitely so, because, so far at least, no human body-plus-intelligence has been resilient enough to keep itself or any other body from eventually dying.
Ecosystems are also remarkably resilient, with multiple species hold-

ing each other in check, moving around in space, multiplying or declining over time in response to weather and the availability of nutrients and the impacts of human activities. Populations and ecosystems also have the ability to "learn" and evolve through their incredibly rich genetic variability. They can, given enough time, come up with whole new systems to take advantage of changing opportunities for life support.
随着时间的推移,种群和生态系统会随着天气、营养物质的供应以及人类活动的影响而相互制约、在空间中移动、繁殖或衰退。种群和生态系统还具有 "学习 "能力,并通过其极其丰富的基因变异性不断进化。只要有足够的时间,它们就能创造出全新的系统,利用不断变化的机会维持生命。
Resilience is not the same thing as being static or constant over time. Resilient systems can be very dynamic. Short-term oscillations, or periodic outbreaks, or long cycles of succession, climax, and collapse may in fact be the normal condition, which resilience acts to restore!
And, conversely, systems that are constant over time can be unresilient. This distinction between static stability and resilience is important. Static stability is something you can see; it's measured by variation in the condition of a system week by week or year by year. Resilience is something that may be very hard to see, unless you exceed its limits, overwhelm and damage the balancing loops, and the system structure breaks down. Because resilience may not be obvious without a whole-system view, people often sacrifice resilience for stability, or for productivity, or for some other more immediately recognizable system property.
  • Injections of genetically engineered bovine growth hormone increase the milk production of a cow without proportionately increasing the cow's food intake. The hormone diverts some of the cow's metabolic energy from other bodily functions to milk production. (Cattle breeding over centuries has done much the same thing but not to the same degree.) The cost of increased production is lowered resilience. The cow is less healthy, less long-lived, more dependent on human management.
  • Just-in-time deliveries of products to retailers or parts to manufacturers have reduced inventory instabilities and brought down costs in many industries. The just-in-time model also has made the production system more vulnerable, however, to perturbations in fuel supply, traffic flow, computer breakdown, labor availability, and other possible glitches.
  • Hundreds of years of intensive management of the forests of Europe gradually have replaced native ecosystems with singleage, single-species plantations, often of nonnative trees. These

    forests are designed to yield wood and pulp at a high rate indefinitely. However, without multiple species interacting with each other and drawing and returning varying combinations of nutrients from the soil, these forests have lost their resilience. They seem to be especially vulnerable to a new form of insult: industrial air pollution.
Many chronic diseases, such as cancer and heart disease, come from breakdown of resilience mechanisms that repair DNA, keep blood vessels flexible, or control cell division. Ecological disasters in many places come from loss of resilience, as species are removed from ecosystems, soil chemistry and biology are disturbed, or toxins build up. Large organizations of all kinds, from corporations to governments, lose their resilience simply because the feedback mechanisms by which they sense and respond to their environment have to travel through too many layers of delay and distortion. (More on that in a minute, when we come to hierarchies.)
许多慢性疾病,如癌症和心脏病,都是由于修复 DNA、保持血管弹性或控制细胞分裂的复原机制遭到破坏所致。许多地方的生态灾难都源于复原力的丧失,因为生态系统中的物种被移除,土壤化学和生物学受到干扰,或者毒素积聚。从企业到政府,各种大型组织都会丧失其复原力,原因很简单,因为它们感知和响应环境的反馈机制必须经过太多的延迟和扭曲。(关于这一点,我们稍后将讨论等级制度)。
I think of resilience as a plateau upon which the system can play, performing its normal functions in safety. A resilient system has a big plateau, a lot of space over which it can wander, with gentle, elastic walls that will bounce it back, if it comes near a dangerous edge.
Systems need to be managed not only for productivity or stability, they also need to be managed for resiliencethe ability to recover from perturbation, the ability to restore or repair themselves.

As a system loses its resilience, its plateau shrinks, and its protective walls become lower and more rigid, until the system is operating on a knifeedge, likely to fall off in one direction or another whenever it makes a move. Loss of resilience can come as a surprise, because the system usually is paying much more attention to its play than to its playing space. One day it does something it has done a hundred times before and crashes.
Awareness of resilience enables one to see many ways to preserve or enhance a system's own restorative powers. That awareness is behind the encouragement of natural ecosystems on farms, so that predators can take on more of the job of controlling pests. It is behind "holistic" health care that tries not only to cure disease but also to build up a body's internal resistance. It is behind aid programs that do more than give food or money-that try to change the circumstances that obstruct peoples' ability to provide their own food or money.
对恢复力的认识使人们能够看到许多保护或增强系统自身恢复力的方法。这种意识的背后是对农场自然生态系统的鼓励,这样捕食者就可以承担更多控制害虫的工作。这就是 "整体 "保健的背后,它不仅试图治疗疾病,还试图增强人体的内部抵抗力。援助计划不仅仅是提供食物或金钱,而是试图改变阻碍人们自己提供食物或金钱的环境。

Self-Organization 自我组织

[Evolution] appears to be not a series of accidents the course of which is determined only by the change of environments during earth history and the resulting struggle for existence, . . . but is governed by definite laws. . . . The discovery of these laws constitutes one of the most important tasks of the future.
[进化]似乎并不是一系列的偶然事件,其过程仅仅是由地球历史上环境的变化和由此产生的生存斗争决定的,......而是受明确规律支配的。. . .发现这些规律是未来最重要的任务之一。
—Ludwig von Bertalanffy, biologist
路德维希-冯-贝尔塔兰菲, 生物学家
The most marvelous characteristic of some complex systems is their ability to learn, diversify, complexify, evolve. It is the ability of a single fertilized ovum to generate, out of itself, the incredible complexity of a mature frog, or chicken, or person. It is the ability of nature to have diversified millions of fantastic species out of a puddle of organic chemicals. It is the ability of a society to take the ideas of burning coal, making steam, pumping water, and specializing labor, and develop them eventually into an automobile assembly plant, a city of skyscrapers, a worldwide network of communications.
This capacity of a system to make its own structure more complex is called self-organization. You see self-organization in a small, mechanistic way whenever you see a snowflake, or ice feathers on a poorly insulated window, or a supersaturated solution suddenly forming a garden of crystals. You see self-organization in a more profound way whenever a seed sprouts, or a baby learns to speak, or a neighborhood decides to come together to oppose a toxic waste dump.
Self-organization is such a common property, particularly of living systems, that we take it for granted. If we didn't, we would be dazzled by the unfolding systems of our world. And if we weren't nearly blind to the property of self-organization, we would do better at encouraging, rather than destroying, the self-organizing capacities of the systems of which we are a part.
Like resilience, self-organization is often sacrificed for purposes of short-term productivity and stability. Productivity and stability are the usual excuses for turning creative human beings into mechanical adjuncts to production processes. Or for narrowing the genetic variability of crop plants. Or for establishing bureaucracies and theories of knowledge that treat people as if they were only numbers.
Self-organization produces heterogeneity and unpredictability. It is likely

to come up with whole new structures, whole new ways of doing things. It requires freedom and experimentation, and a certain amount of disorder. These conditions that encourage self-organization often can be scary for individuals and threatening to power structures. As a consequence, education systems may restrict the creative powers of children instead of stimulating those powers. Economic policies may lean toward supporting established, powerful enterprises rather than upstart, new ones. And many governments prefer their people not to be too self-organizing.
Fortunately, self-organization is such a basic property of living systems that even the most overbearing power structure can never fully kill it, although in the name of law and order, self-organization can be suppressed for long, barren, cruel, boring periods.
Systems theorists used to think that self-organization was such a complex property of systems that it could never be understood. Computers were used to model mechanistic, "deterministic" systems, not evolutionary ones, because it was suspected, without much thought, that evolutionary systems were simply not understandable.
系统理论学家曾经认为,自组织是系统的一个复杂属性,永远无法理解。计算机被用来模拟机械的、"确定性 "的系统,而不是进化系统,因为人们不假思索地怀疑,进化系统根本无法理解。
New discoveries, however, suggest that just a few simple organizing principles can lead to wildly diverse self-organizing structures. Imagine a triangle with three equal sides. Add to the middle of each side another equilateral triangle, one-third the size of the first one. Add to each of the new sides another triangle, one-third smaller. And so on. The result is called a Koch snowflake. (See Figure 46.) Its edge has tremendous length—but it can be contained within a circle. This structure is one simple example of fractal geometry-a realm of mathematics and art populated by elaborate shapes formed by relatively simple rules.
Similarly, the delicate, beautiful, intricate structure of a stylized fern can be generated by a computer with just a few simple fractal rules. The

Figure 46. Even a delicate and intricate pattern, such as the Koch snowflake shown here, can evolve from a simple set of organizing principles or decision rules.
图 46.即使是精致复杂的图案,如图中的科赫雪花,也可以从一套简单的组织原则或决策规则演变而来。

differentiation of a single cell into a human being probably proceeds by some similar set of geometric rules, basically simple, but generating utter complexity. (It is because of fractal geometry that the average human lung has enough surface area to cover a tennis court.)
Here are some other examples of simple organizing rules that have led to self-organizing systems of great complexity:
  • All of life, from viruses to redwood trees, from amoebas to elephants, is based on the basic organizing rules encapsulated in the chemistry of DNA, RNA, and protein molecules.
    所有的生命,从病毒到红杉树,从变形虫到大象,都是基于 DNA、RNA 和蛋白质分子化学所包含的基本组织规则。
  • The agricultural revolution and all that followed started with the simple, shocking ideas that people could stay settled in one place, own land, select and cultivate crops.
-"God created the universe with the earth at its center, the land with the castle at its center, and humanity with the Church at its center"-the organizing principle for the elaborate social and physical structures of Europe in the Middle Ages.
-"God and morality are outmoded ideas; people should be objective and scientific, should own and multiply the means of production, and should treat people and nature as instrumental inputs to production"-the organizing principles of the Industrial Revolution.
Out of simple rules of self-organization can grow enormous, diversifying crystals of technology, physical structures, organizations, and cultures.
Science knows now that self-organizing systems can arise from simple rules. Science, itself a self-organizing system, likes to think that all the complexity of the world must arise, ultimately, from simple rules. Whether that actually happens is something that science does not yet know.

Systems often have the property of self-organization-the ability to structure themselves, to create new structure, to learn, diversify, and complexify. Even complex forms of self-organization may arise from relatively simple organizing rules-or may not.

    • hone our abilities to understand parts,
  1. "Definitions of words in bold face can be found in the Glossary.