Some of my earlier published papers

Some of my earlier published papers

Below is a list of my papers which have been published in referred journals or as technical paper.  All of the work was done by me during my post graduate studies at Western Michigan University, Kalamazoo, Michigan, USA.  I was there since 1987 to 1991.

My research projects included:

  • Paper Recycling
  • Paper Color modeling and prediction
  • Simulation Modeling and Analysis of a Just In Time production system

Based on my research, I was awarded All University Graduate Creative and Research Scholar award by the University and was given a Award Citation by the University President in a Award Ceremony.

 

Effect of Recycling on the Physical Properties of Specific Fibers and Their Networks,”

by John F. Bobalek and Mayank Chaturvedi. In Proceedings, 1988 TAPPI Pulping Conference, p. 183-187.

 

 

Bobalek, John F., and Mayank Chaturvedi. 1989.

“The Effects of Recycling on the Physical Properties of Handsheets with Respect to Specific Wood Species.”

Tappi Journal June: 123- 125.

 

http://imisrise.tappi.org/TAPPI/Products/89/JUN/89JUN123.aspx

 

 

PREDICTION OF PAPER COLOR: A PROCESS SIMULATION APPROACH

WMU Masters Thesis 890

http://scholarworks.wmich.edu/masters_theses/890/

 

 

PREDICTION OF PAPER COLOR: A PROCESS SIMULATION APPROACH

IPST Technical Paper 469

https://smartech.gatech.edu/bitstream/handle/1853/2105/tps-469.pdf

 

 

PREDICTION OF PAPER COLOR: A PROCESS SIMULATION APPROACH

IPST Annual Research Review

 

https://smartech.gatech.edu/bitstream/handle/1853/179/a31667.pdf

 

 

Simulation modelling and analysis of a JIT production system

Mayank Chaturvedi, Damodar Y Golhar
1992/1/1
Production Planning & Control
Volume 3 Issue 1 Pages 81-92
Taylor & Francis Group

Short term Thinking in Investment Decisions of Businesses and Financial Markets

Short term Thinking in Investment Decisions of Businesses and Financial Markets

 

When companies buyback shares and pay dividends rather than investing in new capacity, it leads to low economic growth and low aggregate demand.

Central Banks respond by cutting interest rates.  Yet Businesses do not invest in new capacity.

Many studies attribute this to short term thinking dominant in corporate investment decisions.  Pressures from shareholders push corporate managers to be short term oriented.

Many economists and thinkers have criticized this recently as advanced economies are suffering from anemic growth.

Larry Summers has invoked Secular Stagnation.  He says one of the reason for Secular Stagnation is short term thinking.

Andy Haldane of Bank of England has criticized short term thinking as it prevents investments and causes low economic growth.

Key Terms:

  • Quarterly Capitalism
  • Secular Stagnation
  • Short Term Thinking
  • Low Economic Growth
  • Business Investments
  • Real Interest Rates
  • Monetary Policy
  • Income and Wealth Inequality
  • Aggregate Demand
  • Productive Capacity
  • Productivity growth
  • Long Term Investments
  • Share Buybacks
  • Dividends
  • Corporate Cash Pools

 

Capitalism for the Long Term

The near meltdown of the financial system and the ensuing Great Recession have been, and will remain, the defining issue for the current generation of executives. Now that the worst seems to be behind us, it’s tempting to feel deep relief—and a strong desire to return to the comfort of business as usual. But that is simply not an option. In the past three years we’ve already seen a dramatic acceleration in the shifting balance of power between the developed West and the emerging East, a rise in populist politics and social stresses in a number of countries, and significant strains on global governance systems. As the fallout from the crisis continues, we’re likely to see increased geopolitical rivalries, new international security challenges, and rising tensions from trade, migration, and resource competition. For business leaders, however, the most consequential outcome of the crisis is the challenge to capitalism itself.

That challenge did not just arise in the wake of the Great Recession. Recall that trust in business hit historically low levels more than a decade ago. But the crisis and the surge in public antagonism it unleashed have exacerbated the friction between business and society. On top of anxiety about persistent problems such as rising income inequality, we now confront understandable anger over high unemployment, spiraling budget deficits, and a host of other issues. Governments feel pressure to reach ever deeper inside businesses to exert control and prevent another system-shattering event.

My goal here is not to offer yet another assessment of the actions policymakers have taken or will take as they try to help restart global growth. The audience I want to engage is my fellow business leaders. After all, much of what went awry before and after the crisis stemmed from failures of governance, decision making, and leadership within companies. These are failures we can and should address ourselves.

In an ongoing effort that started 18 months ago, I’ve met with more than 400 business and government leaders across the globe. Those conversations have reinforced my strong sense that, despite a certain amount of frustration on each side, the two groups share the belief that capitalism has been and can continue to be the greatest engine of prosperity ever devised—and that we will need it to be at the top of its job-creating, wealth-generating game in the years to come. At the same time, there is growing concern that if the fundamental issues revealed in the crisis remain unaddressed and the system fails again, the social contract between the capitalist system and the citizenry may truly rupture, with unpredictable but severely damaging results.

Most important, the dialogue has clarified for me the nature of the deep reform that I believe business must lead—nothing less than a shift from what I call quarterly capitalism to what might be referred to as long-term capitalism. (For a rough definition of “long term,” think of the time required to invest in and build a profitable new business, which McKinsey research suggests is at least five to seven years.) This shift is not just about persistently thinking and acting with a next-generation view—although that’s a key part of it. It’s about rewiring the fundamental ways we govern, manage, and lead corporations. It’s also about changing how we view business’s value and its role in society.

There are three essential elements of the shift. First, business and finance must jettison their short-term orientation and revamp incentives and structures in order to focus their organizations on the long term. Second, executives must infuse their organizations with the perspective that serving the interests of all major stakeholders—employees, suppliers, customers, creditors, communities, the environment—is not at odds with the goal of maximizing corporate value; on the contrary, it’s essential to achieving that goal. Third, public companies must cure the ills stemming from dispersed and disengaged ownership by bolstering boards’ ability to govern like owners.

When making major decisions, Asians typically think in terms of at least 10 to 15 years. In the U.S. and Europe, nearsightedness is the norm.

None of these ideas, or the specific proposals that follow, are new. What is new is the urgency of the challenge. Business leaders today face a choice: We can reform capitalism, or we can let capitalism be reformed for us, through political measures and the pressures of an angry public. The good news is that the reforms will not only increase trust in the system; they will also strengthen the system itself. They will unleash the innovation needed to tackle the world’s grand challenges, pave the way for a new era of shared prosperity, and restore public faith in business.

1. Fight the Tyranny of Short-Termism

As a Canadian who for 25 years has counseled business, public sector, and nonprofit leaders across the globe (I’ve lived in Toronto, Sydney, Seoul, Shanghai, and now London), I’ve had a privileged glimpse into different societies’ values and how leaders in various cultures think. In my view, the most striking difference between East and West is the time frame leaders consider when making major decisions. Asians typically think in terms of at least 10 to 15 years. For example, in my discussions with the South Korean president Lee Myung-bak shortly after his election in 2008, he asked us to help come up with a 60-year view of his country’s future (though we settled for producing a study called National Vision 2020.) In the U.S. and Europe, nearsightedness is the norm. I believe that having a long-term perspective is the competitive advantage of many Asian economies and businesses today.

Myopia plagues Western institutions in every sector. In business, the mania over quarterly earnings consumes extraordinary amounts of senior time and attention. Average CEO tenure has dropped from 10 to six years since 1995, even as the complexity and scale of firms have grown. In politics, democracies lurch from election to election, with candidates proffering dubious short-term panaceas while letting long-term woes in areas such as economic competitiveness, health, and education fester. Even philanthropy often exhibits a fetish for the short term and the new, with grantees expected to become self-sustaining in just a few years.

Lost in the frenzy is the notion that long-term thinking is essential for long-term success. Consider Toyota, whose journey to world-class manufacturing excellence was years in the making. Throughout the 1950s and 1960s it endured low to nonexistent sales in the U.S.—and it even stopped exporting altogether for one bleak four-year period—before finally emerging in the following decades as a global leader. Think of Hyundai, which experienced quality problems in the late 1990s but made a comeback by reengineering its cars for long-term value—a strategy exemplified by its unprecedented introduction, in 1999, of a 10-year car warranty. That radical move, viewed by some observers as a formula for disaster, helped Hyundai quadruple U.S. sales in three years and paved the way for its surprising entry into the luxury market.

To be sure, long-term perspectives can be found in the West as well. For example, in 1985, in the face of fierce Japanese competition, Intel famously decided to abandon its core business, memory chips, and focus on the then-emerging business of microprocessors. This “wrenching” decision was “nearly inconceivable” at the time, says Andy Grove, who was then the company’s president. Yet by making it, Intel emerged in a few years on top of a new multi-billion-dollar industry. Apple represents another case in point. The iPod, released in 2001, sold just 400,000 units in its first year, during which Apple’s share price fell by roughly 25%. But the board took the long view. By late 2009 the company had sold 220 million iPods—and revolutionized the music business.

It’s fair to say, however, that such stories are countercultural. In the 1970s the average holding period for U.S. equities was about seven years; now it’s more like seven months. According to a recent paper by Andrew Haldane, of the Bank of England, such churning has made markets far more volatile and produced yawning gaps between corporations’ market price and their actual value. Then there are the “hyperspeed” traders (some of whom hold stocks for only a few seconds), who now account for 70% of all U.S. equities trading, by one estimate. In response to these trends, executives must do a better job of filtering input, and should give more weight to the views of investors with a longer-term, buy-and-hold orientation.

If they don’t, short-term capital will beget short-term management through a natural chain of incentives and influence. If CEOs miss their quarterly earnings targets, some big investors agitate for their removal. As a result, CEOs and their top teams work overtime to meet those targets. The unintended upshot is that they manage for only a small portion of their firm’s value. When McKinsey’s finance experts deconstruct the value expectations embedded in share prices, we typically find that 70% to 90% of a company’s value is related to cash flows expected three or more years out. If the vast majority of most firms’ value depends on results more than three years from now, but management is preoccupied with what’s reportable three months from now, then capitalism has a problem.

Roughly 70% of all U.S. equities trading is now done by “hyperspeed” traders—some of whom hold stocks for only a few seconds.

Some rightly resist playing this game. Unilever, Coca-Cola, and Ford, to name just a few, have stopped issuing earnings guidance altogether. Google never did. IBM has created five-year road maps to encourage investors to focus more on whether it will reach its long-term earnings targets than on whether it exceeds or misses this quarter’s target by a few pennies. “I can easily make my numbers by cutting SG&A or R&D, but then we wouldn’t get the innovations we need,” IBM’s CEO, Sam Palmisano, told us recently. Mark Wiseman, executive vice president at the Canada Pension Plan Investment Board, advocates investing “for the next quarter century,” not the next quarter. And Warren Buffett has quipped that his ideal holding period is “forever.” Still, these remain admirable exceptions.

To break free of the tyranny of short-termism, we must start with those who provide capital. Taken together, pension funds, insurance companies, mutual funds, and sovereign wealth funds hold $65 trillion, or roughly 35% of the world’s financial assets. If these players focus too much attention on the short term, capitalism as a whole will, too.

In theory they shouldn’t, because the beneficiaries of these funds have an obvious interest in long-term value creation. But although today’s standard practices arose from the desire to have a defensible, measurable approach to portfolio management, they have ended up encouraging shortsightedness. Fund trustees, often advised by investment consultants, assess their money managers’ performance relative to benchmark indices and offer only short-term contracts. Those managers’ compensation is linked to the amount of assets they manage, which typically rises when short-term performance is strong. Not surprisingly, then, money managers focus on such performance—and pass this emphasis along to the companies in which they invest. And so it goes, on down the line.

Only 45% of those surveyed in the U.S. and the UK expressed trust in business. This stands in stark contrast to developing countries: For example, the figure is 61% in China, 70% in India, and 81% in Brazil.

As the stewardship advocate Simon Wong points out, under the current system pension funds deem an asset manager who returns 10% to have underperformed if the relevant benchmark index rises by 12%. Would it be unthinkable for institutional investors instead to live with absolute gains on the (perfectly healthy) order of 10%—especially if they like the approach that delivered those gains—and review performance every three or five years, instead of dropping the 10-percenter? Might these big funds set targets for the number of holdings and rates of turnover, at least within the “fundamental investing” portion of their portfolios, and more aggressively monitor those targets? More radically, might they end the practice of holding thousands of stocks and achieve the benefits of diversification with fewer than a hundred—thereby increasing their capacity to effectively engage with the businesses they own and improve long-term performance? Finally, could institutional investors beef up their internal skills and staff to better execute such an agenda? These are the kinds of questions we need to address if we want to align capital’s interests more closely with capitalism’s.

2. Serve Stakeholders, Enrich Shareholders

The second imperative for renewing capitalism is disseminating the idea that serving stakeholders is essential to maximizing corporate value. Too often these aims are presented as being in tension: You’re either a champion of shareholder value or you’re a fan of the stakeholders. This is a false choice.

The inspiration for shareholder-value maximization, an idea that took hold in the 1970s and 1980s, was reasonable: Without some overarching financial goal with which to guide and gauge a firm’s performance, critics feared, managers could divert corporate resources to serve their own interests rather than the owners’. In fact, in the absence of concrete targets, management might become an exercise in politics and stakeholder engagement an excuse for inefficiency. Although this thinking was quickly caricatured in popular culture as the doctrine of “greed is good,” and was further tarnished by some companies’ destructive practices in its name, in truth there was never any inherent tension between creating value and serving the interests of employees, suppliers, customers, creditors, communities, and the environment. Indeed, thoughtful advocates of value maximization have always insisted that it is long-term value that has to be maximized.

Capitalism’s founding philosopher voiced an even bolder aspiration. “All the members of human society stand in need of each others assistance, and are likewise exposed to mutual injuries,” Adam Smith wrote in his 1759 work, The Theory of Moral Sentiments. “The wise and virtuous man,” he added, “is at all times willing that his own private interest should be sacrificed to the public interest,” should circumstances so demand.

Smith’s insight into the profound interdependence between business and society, and how that interdependence relates to long-term value creation, still reverberates. In 2008 and again in 2010, McKinsey surveyed nearly 2,000 executives and investors; more than 75% said that environmental, social, and governance (ESG) initiatives create corporate value in the long term. Companies that bring a real stakeholder perspective into corporate strategy can generate tangible value even sooner. (See the sidebar “Who’s Getting It Right?”)

Creating direct business value, however, is not the only or even the strongest argument for taking a societal perspective. Capitalism depends on public trust for its legitimacy and its very survival. According to the Edelman public relations agency’s just-released 2011 Trust Barometer, trust in business in the U.S. and the UK (although up from mid-crisis record lows) is only in the vicinity of 45%. This stands in stark contrast to developing countries: For example, the figure is 61% in China, 70% in India, and 81% in Brazil. The picture is equally bleak for individual corporations in the Anglo-American world, “which saw their trust rankings drop again last year to near-crisis lows,” says Richard Edelman.

How can business leaders restore the public’s trust? Many Western executives find that nothing in their careers has prepared them for this new challenge. Lee Scott, Walmart’s former CEO, has been refreshingly candid about arriving in the top job with a serious blind spot. He was plenty busy minding the store, he says, and had little feel for the need to engage as a statesman with groups that expected something more from the world’s largest company. Fortunately, Scott was a fast learner, and Walmart has become a leader in environmental and health care issues.

Tomorrow’s CEOs will have to be, in Joseph Nye’s apt phrase, “tri-sector athletes”: able and experienced in business, government, and the social sector. But the pervading mind-set gets in the way of building those leadership and management muscles. “Analysts and investors are focused on the short term,” one executive told me recently. “They believe social initiatives don’t create value in the near term.” In other words, although a large majority of executives believe that social initiatives create value in the long term, they don’t act on this belief, out of fear that financial markets might frown. Getting capital more aligned with capitalism should help businesses enrich shareholders by better serving stakeholders.

3. Act Like You Own the Place

As the financial sector’s troubles vividly exposed, when ownership is broadly fragmented, no one acts like he’s in charge. Boards, as they currently operate, don’t begin to serve as a sufficient proxy. All the Devils Are Here, by Bethany McLean and Joe Nocera, describes how little awareness Merrill Lynch’s board had of the firm’s soaring exposure to subprime mortgage instruments until it was too late. “I actually don’t think risk management failed,” Larry Fink, the CEO of the investment firm BlackRock, said during a 2009 debate about the future of capitalism, sponsored by the Financial Times. “I think corporate governance failed, because…the boards didn’t ask the right questions.”

What McKinsey has learned from studying successful family-owned companies suggests a way forward: The most effective ownership structure tends to combine some exposure in the public markets (for the discipline and capital access that exposure helps provide) with a significant, committed, long-term owner. Most large public companies, however, have extremely dispersed ownership, and boards rarely perform the single-owner-proxy role. As a result, CEOs too often listen to the investors (and members of the media) who make the most noise. Unfortunately, those parties tend to be the most nearsighted ones. And so the tyranny of the short term is reinforced.

The answer is to renew corporate governance by rooting it in committed owners and by giving those owners effective mechanisms with which to influence management. We call this ownership-based governance, and it requires three things:

Just 43% of the nonexecutive directors of public companies believe they significantly influence strategy. For this to change, board members must devote much more time to their roles.

More-effective boards.

In the absence of a dominant shareholder (and many times when there is one), the board must represent a firm’s owners and serve as the agent of long-term value creation. Even among family firms, the executives of the top-performing companies wield their influence through the board. But only 43% of the nonexecutive directors of public companies believe they significantly influence strategy. For this to change, board members must devote much more time to their roles. A government-commissioned review of the governance of British banks last year recommended an enormous increase in the time required of nonexecutive directors of banks—from the current average, between 12 and 20 days annually, to between 30 and 36 days annually. What’s especially needed is an increase in the informal time board members spend with investors and executives. The nonexecutive board directors of companies owned by private equity firms spend 54 days a year, on average, attending to the company’s business, and 70% of that time consists of informal meetings and conversations. Four to five days a month obviously give a board member much greater understanding and impact than the three days a quarter (of which two may be spent in transit) devoted by the typical board member of a public company.

Boards also need much more relevant experience. Industry knowledge—which four of five nonexecutive directors of big companies lack—helps boards identify immediate opportunities and reduce risk. Contextual knowledge about the development path of an industry—for example, whether the industry is facing consolidation, disruption from new technologies, or increased regulation—is highly valuable, too. Such insight is often obtained from experience with other industries that have undergone a similar evolution.

In addition, boards need more-effective committee structures—obtainable through, for example, the establishment of a strategy committee or of dedicated committees for large business units. Directors also need the resources to allow them to form independent views on strategy, risk, and performance (perhaps by having a small analytical staff that reports only to them). This agenda implies a certain professionalization of nonexecutive directorships and a more meaningful strategic partnership between boards and top management. It may not please some executive teams accustomed to boards they can easily “manage.” But given the failures of governance to date, it is a necessary change.

More-sensible CEO pay.

An important task of governance is setting executive compensation. Although 70% of board directors say that pay should be tied more closely to performance, CEO pay is too often structured to reward a leader simply for having made it to the top, not for what he or she does once there. Meanwhile, polls show that the disconnect between pay and performance is contributing to the decline in public esteem for business.

Companies should create real risk for executives.Some experts privately suggest mandating that new executives invest a year’s salary in the company.

CEOs and other executives should be paid to act like owners. Once upon a time we thought that stock options would achieve this result, but stock-option- based compensation schemes have largely incentivized the wrong behavior. When short-dated, options lead to a focus on meeting quarterly earnings estimates; even when long-dated (those that vest after three years or more), they can reward managers for simply surfing industry- or economy-wide trends (although reviewing performance against an appropriate peer index can help minimize free rides). Moreover, few compensation schemes carry consequences for failure—something that became clear during the financial crisis, when many of the leaders of failed institutions retired as wealthy people.

There will never be a one-size-fits-all solution to this complex issue, but companies should push for change in three key areas:

• They should link compensation to the fundamental drivers of long-term value, such as innovation and efficiency, not just to share price.

• They should extend the time frame for executive evaluations—for example, using rolling three-year performance evaluations, or requiring five-year plans and tracking performance relative to plan. This would, of course, require an effective board that is engaged in strategy formation.

• They should create real downside risk for executives, perhaps by requiring them to put some skin in the game. Some experts we’ve surveyed have privately suggested mandating that new executives invest a year’s salary in the company.

Redefined shareholder “democracy.”

The huge increase in equity churn in recent decades has spawned an anomaly of governance: At any annual meeting, a large number of those voting may soon no longer be shareholders. The advent of high-frequency trading will only worsen this trend. High churn rates, short holding periods, and vote-buying practices may mean the demise of the “one share, one vote” principle of governance, at least in some circumstances. Indeed, many large, top-performing companies, such as Google, have never adhered to it. Maybe it’s time for new rules that would give greater weight to long-term owners, like the rule in some French companies that gives two votes to shares held longer than a year. Or maybe it would make sense to assign voting rights based on the average turnover of an investor’s portfolio. If we want capitalism to focus on the long term, updating our notions of shareholder democracy in such ways will soon seem less like heresy and more like common sense.

While I remain convinced that capitalism is the economic system best suited to advancing the human condition, I’m equally persuaded that it must be renewed, both to deal with the stresses and volatility ahead and to restore business’s standing as a force for good, worthy of the public’s trust. The deficiencies of the quarterly capitalism of the past few decades were not deficiencies in capitalism itself—just in that particular variant. By rebuilding capitalism for the long term, we can make it stronger, more resilient, more equitable, and better able to deliver the sustainable growth the world needs. The three imperatives outlined above can be a start along this path and, I hope, a way to launch the conversation; others will have their own ideas to add.

The kind of deep-seated, systemic changes I’m calling for can be achieved only if boards, business executives, and investors around the world take responsibility for bettering the system they lead. Such changes will not be easy; they are bound to encounter resistance, and business leaders today have more than enough to do just to keep their companies running well. We must make the effort regardless. If capitalism emerges from the crisis vibrant and renewed, future generations will thank us. But if we merely paper over the cracks and return to our precrisis views, we will not want to read what the historians of the future will write. The time to reflect—and to act—is now.

 

Please see my other related posts.

Business Investments and Low Interest Rates

Mergers and Acquisitions – Long Term Trends and Waves

 

 

Key sources of Research:

Secular stagnation and low investment: Breaking the vicious cycle—a discussion paper

McKinsey

http://www.mckinsey.com/global-themes/europe/secular-stagnation-and-low-investment-breaking-the-vicious-cycle

Case Still Out on Whether Corporate Short-Termism Is a Problem

Larry Summers

http://larrysummers.com/2017/02/09/case-still-out-on-whether-corporate-short-termism-is-a-problem/

Where companies with a long-term view outperform their peers

McKinsey

http://www.mckinsey.com/global-themes/long-term-capitalism/where-companies-with-a-long-term-view-outperform-their-peers

How short-term thinking hampers long-term economic growth

FT

https://www.ft.com/content/8c868a98-b821-11e4-b6a5-00144feab7de

Anthony Hilton: Short-term thinking hits nations as a whole, not just big business

http://www.standard.co.uk/comment/comment/anthony-hilton-short-term-thinking-hits-nations-as-a-whole-not-just-big-business-10427294.html

Short-termism in business: causes, mechanisms and consequences

EY Poland Report

http://www.ey.com/Publication/vwLUAssets/EY_Poland_Report/$FILE/Short-termism_raport_EY.pdf

Overcoming the Barriers to Long-term Thinking in Financial Markets

Ruth Curran and Alice Chapple
Forum for the Future

https://www.forumforthefuture.org/sites/default/files/project/downloads/long-term-thinking-fpf-report-july-11.pdf

Understanding Short-Termism: Questions and Consequences

http://rooseveltinstitute.org/wp-content/uploads/2015/11/Understanding-Short-Termism.pdf

Ending Short-Termism : An Investment Agenda for Growth

http://rooseveltinstitute.org/wp-content/uploads/2015/11/Ending-Short-Termism.pdf

The Short Long

Speech by
Andrew G Haldane, Executive Director, Financial Stability, and Richard Davies

Brussels May 2011

http://www.bankofengland.co.uk/archive/Documents/historicpubs/speeches/2011/speech495.pdf

Capitalism for the Long Term

Dominic Barton

From the March 2011 Issue

https://hbr.org/2011/03/capitalism-for-the-long-term

Quarterly capitalism: The pervasive effects of short-termism and austerity

https://currentlyunderdevelopment.wordpress.com/2016/05/10/quarterly-capitalism-the-pervasive-effects-of-short-termism-and-austerity/

Is Short-Term Behavior Jeopardizing the Future Prosperity of Business?

http://www.wlrk.com/docs/IsShortTermBehaviorJeopardizingTheFutureProsperityOfBusiness_CEOStrategicimplications.pdf

Andrew G Haldane: The short long

Speech by Mr Andrew Haldane, Executive Director, Financial Stability, and Mr Richard
Davies, Economist, Financial Institutions Division, Bank of England,
at the 29th Société
Universitaire Européene de Recherches Financières Colloquium,
Brussels, 11 May 2011

http://www.bis.org/review/r110511e.pdf

THE UNEASY CASE FOR FAVORING LONG-TERM SHAREHOLDERS

Jesse M. Fried

https://dash.harvard.edu/bitstream/handle/1/17985223/Fried_795.pdf?sequence=1

The fringe economic theory that might get traction in the 2016 campaign

https://www.washingtonpost.com/news/wonk/wp/2015/03/02/the-fringe-economic-theory-that-might-get-traction-in-the-2016-campaign/?utm_term=.932bc0b97758

FCLT Global:  Focusing Capital on the Long Term

Publications

http://www.fcltglobal.org/insights/publications

Finally, Evidence That Managing for the Long Term Pays Off

Dominic Barton

James Manyika

Sarah Keohane Williamson

February 07, 2017 UPDATED February 09, 2017

https://hbr.org/2017/02/finally-proof-that-managing-for-the-long-term-pays-off

Focusing Capital on the Long Term

Dominic Barton

Mark Wiseman

From the January–February 2014 Issue

Is Corporate Short-Termism Really a Problem? The Jury’s Still Out

Lawrence H. Summers

February 16, 2017

Yes, Short-Termism Really Is a Problem

Roger L. Martin

October 09, 2015

Long-Termism or Lemons

The Role of Public Policy in Promoting Long-Term Investments

By Marc Jarsulic, Brendan V. Duke, and Michael Madowitz October 2015

Center for American Progress

https://cdn.americanprogress.org/wp-content/uploads/2015/10/21060054/LongTermism-reportB.pdf

 

Overcoming Short-termism: A Call for A More Responsible Approach to Investment and Business Management

https://corpgov.law.harvard.edu/2009/09/11/overcoming-short-termism-a-call-for-a-more-responsible-approach-to-investment-and-business-management/

 

 

Focusing capital on the Long Term

Jean-Hugues Monier – Senior Parter – McKinsey & Company

Princeton University – November 2016

http://jrc.princeton.edu/sites/jrc/files/jean-hugues_j._monier_slides_final.pdf

Systems Biology: Biological Networks, Network Motifs, Switches and Oscillators

Systems Biology: Biological Networks, Network Motifs, Switches and Oscillators

 

 

From Biological switches and clocks

The living cell receives signals from its environment and its own internal state, processes the information, and initiates appropriate responses in terms of changes in gene expression, cell movement, and cell growth or death. Like a digital computer, information processing within cells is carried out by a complex network of switches and oscillators, but instead of being fabricated from silicon transistors and quartz crystals, the cell’s computer is an evolved network of interacting genes and proteins. In the same way that computer design was made possible by a sophisticated theory of electronic circuitry, a basic understanding of cellular regulatory mechanisms will require a relevant theory of biomolecular circuitry. Although the ‘engineering mindset’ is sorely needed to make sense of the cell’s circuitry, the squishy, sloppy, massively parallel, analogue nature of biochemistry is so different from the solid-state, precise, sequential, digital nature of computers that the mathematical tools and intellectual biases of the solid-state physicist/electrical engineer are not entirely appropriate to unravelling the molecular logic of cell physiology. New modelling paradigms and software tools are evolving to meet the challenges of the new ‘systems biology’ of the living cell.

 

 

System Biology includes study of the following among other areas.

  • Biological Networks
  • Network Motifs
  • Switches
  • Oscillators

 

 

Biological Networks

  • Protein–protein interaction networks
  • Gene regulatory networks (DNA–protein interaction networks)
  • Gene co-expression networks (transcript–transcript association networks)
  • Metabolic networks
  • Signaling networks
  • Neuronal networks
  • Between-species interaction networks
  • Within-species interaction networks

 

Network Motifs:

  • Coherent Feedforward Loop (FFL)
  • Incoherent Feedforward Loop
  • Feedback Loop
  • Scaffold Motifs
  • Bi Fan
  • Multi Input Motifs (MIM)
  • Regulator Chains
  • Bi-Parallel
  • Single Input Module (SIM)
  • Dense Overlapping Regulon (DOR)

 

Biological Switches

  • Ultrasensitivity
  • Switches (Bistability)

 

Biological Oscillators

  • Clocks
  • Negative Feedback Only Oscillators
    • Repressilator
    • Pentilator
    • Goodwin Oscillator
    • Frazilator
    • Metabolator
  • Negative + Positive Feedback Oscillators
    • Meyer and Strayer model of Calcium Oscillations
    • van der Pol Oscillator
    • Fitzhugh-Nagumo Oscillator
    • Cyanobacteria Circadian Oscillator
  • Negative + Negative Feedback Oscillator
  • Negative and Positive + Negative Feedback cell cycle Oscillator
  • Fussenegger Oscillators
  • Smolen Oscillator
  • Amplified Negative Feedback Oscillators
  • Variable link Oscillators

 

Synthetic Biology study design of networks, switches, and oscillators.

 

From The dynamics and robustness of Network Motifs in transcription networks

Network Motifs

Even though biological systems are extremely complex, some of its complexity could be simplified. The study of a complex system in its entirety could prove impossible with current theories and technology. However, mathematical modelling has sought to distil the essence of complexity into concepts readily understandable by today’s science. One of such approaches has been reported by means of the study of pathways of interaction of biological networks. By concentrating on similar features that biological networks share, it has been recently discovered that at a cellular level, regulation and transcription Networks display certain patterns of connectivity at a much higher rate than expected in an equivalent randomized network. These recurring patterns of interaction, or network “Motifs”, can help us define bread classes of networks and their types of functional elements. In the same way, they can reveal the evolutionary aim by which they have been developed. Network Motifs can be interpreted as structures that have emerged as direct a reflection of the constraints under which the network has evolved. These network Motifs have been found in the biological networks of many systems, suggesting that they are the building blocks of transcription networks [4]. It has been suggested that in biological networks, these recurrent Network Motifs are responsible for carrying out key information processing tasks in the organism [5].

 

From Coupling oscillations and switches in genetic networks.

Switches (bistability) and oscillations (limit cycle) are omnipresent in biological networks. Synthetic genetic networks producing bistability and oscillations have been designed and constructed experimentally. However, in real biological systems, regulatory circuits are usually interconnected and the dynamics of those complex networks is often richer than the dynamics of simple modules. Here we couple the genetic Toggle switch and the Repressilator, two prototypic systems exhibiting bistability and oscillations, respectively. We study two types of coupling. In the first type, the bistable switch is under the control of the oscillator. Numerical simulation of this system allows us to determine the conditions under which a periodic switch between the two stable steady states of the Toggle switch occurs. In addition we show how birhythmicity characterized by the coexistence of two stable small-amplitude limit cycles, can easily be obtained in the system. In the second type of coupling, the oscillator is placed under the control of the Toggleswitch. Numerical simulation of this system shows that this construction could for example be exploited to generate a permanent transition from a stable steady state to self-sustained oscillations (and vice versa) after a transient external perturbation. Those results thus describe qualitative dynamical behaviors that can be generated through the coupling of two simple network modules. These results differ from the dynamical properties resulting from interlocked feedback loops systems in which a given variable is involved at the same time in both positive and negative feedbacks. Finally the models described here may be of interest in synthetic biology, as they give hints on how the coupling should be designed to get the required properties.

 

From Robust, Tunable Biological Oscillations from Interlinked Positive and Negative Feedback Loops

To test the generality of the idea that positive feedback enables an oscillator to have a tunable frequency and constant amplitude, we examined several other oscillator models, including five negative feedback–only models: (i) the Goodwin oscillator, a well-studied model relevant to circadian oscillations (18, 19); (ii) the Repressilator, a transcriptional triple-negative feedback loop constructed in Escherichia coli (20); (iii) the “Pentilator,” a Repressilator with five (rather than three) repressors; (iv) the Metabolator (21), a synthetic metabolic oscillator; and (v) the Frzilator, amodel of the control of gliding motions in myxobacteria (22). In four of the cases (Goodwin, Repressilator, Pentilator, and Metabolator), the amplitude/frequency curves were inverted U-shaped curves similar to that seen for the negative feedback–only cell cycle model (Figs. 1B and 3A). In the case of the Frzilator, the legs of the curve were truncated; the oscillator had a nonzero minimal amplitude (Fig. 3A). For all five of the negative feedback–only models, the oscillators functioned over only a narrow range of frequencies (Fig. 3A).

We also examined four positive-plus-negative feedback oscillators: (i) the van der Pol oscillator, inspired by studies of vacuum tubes (12); (ii) the Fitzhugh-Nagumo model of propagating action potentials (23, 24); (iii) the Meyer-Stryer model of calcium oscillations (25); and (iv) a model of circadian oscillations in the cyanobacterial KaiA/B/C system (26–28). In each case, we obtained a flat, wide amplitude/frequency curve (Fig. 3B). Thus, a tunable frequency plus constant amplitude can be obtained from many different positive-plusnegative feedback models; this feature is not peculiar to one particular topology or parameterization.

These findings rationalize why the positiveplus- negative feedback design might have been selected through evolution in cases where a tunable frequency and constant amplitude are important, such as heartbeats and cell cycles. However, it is not clear that an adjustable frequency would be advantageous for circadian oscillations, because frequency is fixed at one cycle per day. Nevertheless, the cyanobacterial circadian oscillator appears to rely on positive feedback (26), and positive feedback loops have been postulated for other circadian oscillators as well (Table 1). This raises the question of whether the positiveplus- negative feedback design might offer additional advantages.

One possibility is that the positive-plusnegative feedback design permits oscillations over a wider range of enzyme concentrations and kinetic constant values, making the oscillator easier to evolve and more robust to variations in its imperfect components. We tested this idea through a Monte Carlo approach.We formulated three simple oscillatormodels: (i) a three-variable triple negative feedback loop with no additional feedback (Fig. 4A), (ii) one with added positive feedback (Fig. 4B), or (iii) one with added negative feedback (Fig. 4C). We generated random parameter sets for the models and then for each set determined whether the model produced limit cycle oscillations.We continued generating parameter sets until we had amassed 500 that gave oscillations.

 

From Robust, Tunable Biological Oscillations from Interlinked Positive and Negative Feedback Loops

Sysbio

 

 

Key Terms:

  • Ultra-sensitivity
  • Bi-stability
  • Positive Feedback Loop
  • Negative Feedback Loop
  • Biological Oscillators
  • Biological Switches
  • Biological Networks
  • Network Motifs
  • Regulation Networks
  • Signalling Networks
  • Communication Networks
  • Biological Clocks
  • Circadian Rhythms
  • Harmonic Oscillators
  • Van der Pol Oscillator (Limit Cycle)
  • FitzHugh–Nagumo oscillators (Neural)
  • Limit Cycle Oscillator
  • Cell Cycle
  • Systems Biology
  • Synthetic Biology
  • Gene Regulatory Networks
  • Kuramoto Oscillators
  • Phase Coupled Oscillators
  • Cardic Pacemaker
  • Biochemical Networks
  • Synchronization
  • Goodwin Oscillator
  • Repressilators
  • Fussenegger Oscillators
  • Smolen Oscillators
  • Variable Link Oscillators
  • Metabolators
  • Amplified Negative Feedback Oscillators

 

 

 

Key Sources of Research:

 

 

Ultrasensitivity Part I: Michaelian responses and zero-order ultrasensitivity

James E. Ferrell Jr. and Sang Hoon Ha

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4214216/pdf/nihms-629459.pdf

 

 

 

 

Ultrasensitivity Part II: Multisite phosphorylation, stoichiometric inhibitors, and positive feedback

James E. Ferrell Jr. and Sang Hoon Ha

 

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4435807/pdf/nihms686079.pdf

 

 

 

Ultrasensitivity part III: cascades, bistable switches, and oscillators

James E. Ferrell Jr and Sang Hoon Ha

 

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4254632/pdf/nihms635216.pdf

 

 

 

Robust Network Topologies for Generating Switch-Like Cellular Responses

Najaf A. Shah1, Casim A. Sarkar

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3121696/pdf/pcbi.1002085.pdf

 

 

 

 

Feedback Loops Shape Cellular Signals in Space and Time

Onn Brandman1 and Tobias Meyer

 

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2680159/pdf/nihms101299.pdf

 

 

 

Interlinked Fast and Slow Positive Feedback Loops Drive Reliable Cell Decisions

Onn Brandman, James E. Ferrell Jr, Rong Li2,3,4, and Tobias Meyer

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3175767/pdf/nihms180881.pdf

 

 

 

Positive feedback in cellular control systems

Alexander Y. Mitrophanov and Eduardo A. Groisman

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2486260/pdf/nihms-58057.pdf

 

 

 

Effect of positive feedback loops on the robustness of oscillations in the network of cyclin-dependent kinases driving the mammalian cell cycle

Claude Gerard, Didier Gonze and Albert Goldbeter

 

http://onlinelibrary.wiley.com/store/10.1111/j.1742-4658.2012.08585.x/asset/j.1742-4658.2012.08585.x.pdf?v=1&t=j0i1rfq0&s=54814f48d70da4b93bd1632677765a1a5673c8d6

 

 

Design Principles of Biochemical Oscillators

Béla Novak and John J. Tyson

 

 

 

Design principles underlying circadian clocks

D. A. Rand1,†, B. V. Shulgin1, D. Salazar1,2 and A. J. Millar

 

 

 

Positive Feedback Promotes Oscillations in Negative Feedback Loops

Bharath Ananthasubramaniam*, Hanspeter Herzel

 

 

 

Efficient Switches in Biology and Computer Science

Luca Cardelli1,2, Rosa D. Hernansaiz-Ballesteros3, Neil Dalchau1, Attila Csika ́sz-Nagy

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5215766/pdf/pcbi.1005100.pdf

 

 

 

Robust, Tunable Biological Oscillations from Interlinked Positive and Negative Feedback Loops

Tony Yu-Chen Tsai,1* Yoon Sup Choi,1,2* Wenzhe Ma,3,4 Joseph R. Pomerening,5 Chao Tang,3,4 James E. Ferrell Jr

https://www.researchgate.net/publication/5253202_Robust_Tunable_Biological_Oscillations_from_Interlinked_Positive_and_Negative_Feedback_Loops?el=1_x_8&enrichId=rgreq-3a45d550364998e0f57384dda12a695f-XXX&enrichSource=Y292ZXJQYWdlOzI0MTY5NjI3MjtBUzoxMzEyODEwMTg5NTM3MjhAMTQwODMxMTI0MjY2OQ==

 

 

 

Biological switches and clocks

John J. Tyson1,*, Reka Albert2, Albert Goldbeter3, Peter Ruoff4 and Jill Sibl

 

http://www.ulb.ac.be/sciences/utc/ARTICLES/2008_Tyson_J_R_Soc_Interface.pdf

https://www.kitp.ucsb.edu/activities/bioclocks07

http://online.kitp.ucsb.edu/online/bioclocks07/

 

 

 

Network thinking in ecology and evolution

Stephen R. Proulx1, Daniel E.L. Promislow2 and Patrick C. Phillips

 

https://pdfs.semanticscholar.org/5665/65601ed2a5c67143b6d4be7193c02235a279.pdf

 

 

 

Networks in ecology

Jordi Bascompte

 

http://izt.ciens.ucv.ve/ecologia/Archivos/ECO_POB%202007/ECOPO7_2007/Bascompte%202007.pdf

 

 

 

Network structure and the biology of populations

Robert M. May

 

https://www.sccs.swarthmore.edu/users/08/bblonder/phys120/docs/may.pdf

 

 

 

Biological networks: Motifs and modules

 

http://bioinfo.vanderbilt.edu/zhanglab/lectures/BMIF310_network_B_Motifs_2009.pdf

 

 

 

Analysis of Biological Networks: Network Motifs

 

http://www.cs.tau.ac.il/~roded/courses/bnet-a06/lec04.pdf

 

 

 

Regulatory networks & Functional motifs

Didier Gonze

 

http://homepages.ulb.ac.be/~dgonze/TEACHING/network_motifs.pdf

 

 

 

Structure and function of the feed-forward loop network motif

S. Mangan and U. Alon

 

http://www.pnas.org/content/100/21/11980.full.pdf

 

 

 

Network Motifs: Simple Building Blocks of Complex Networks

R. Milo, S. Shen-Orr, S. Itzkovitz, N. Kashtan, D. Chklovskii, U. Alon

 

http://wilson.med.harvard.edu/nb204/MiloAlon2002.pdf

 

 

 

The dynamics and robustness of Network Motifs in transcription networks

Arturo Araujo

http://www.ucl.ac.uk/~ucbpaar/flies_archivos/Network_Motifs.pdf

 

 

 

Formation of Regulatory Patterns During Signal Propagation in a Mammalian Cellular Network

Avi Ma’ayan, Sherry L. Jenkins, Susana Neves, Anthony Hasseldine, Elizabeth Grace, Benjamin Dubin-Thaler, Narat J. Eungdamrong, Gehzi Weng, Prahlad T. Ram, J. Jeremy Rice, Aaron Kershenbaum, Gustavo A. Stolovitzky, Robert D. Blitzer, and Ravi Iyengar

 

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3032439/pdf/nihms266526.pdf

 

 

 

Toward Predictive Models of Mammalian Cells

Avi Ma’ayan, Robert D. Blitzer, and Ravi Iyengar

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3035045/pdf/nihms266522.pdf

 

 

 

Modeling Cell Signaling Networks

Narat J. Eungdamrong and Ravi Iyengar

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3620715/pdf/nihms453834.pdf

 

 

 

Bistability in Biochemical Signaling Models

Eric A. Sobie

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4118931/pdf/nihms-332970.pdf

 

 

An Introduction to Dynamical Systems

Eric A. Sobie

 

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4118930/pdf/nihms-332968.pdf

 

 

 

Computational approaches for modeling regulatory cellular networks

Narat J. Eungdamrong and Ravi Iyengar

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3619405/pdf/nihms-453838.pdf

 

 

Systems Biology—Biomedical Modeling

Eric A. Sobie,* Young-Seon Lee, Sherry L. Jenkins, and Ravi Iyengar

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3188945/

 

 

 

Network analyses in systems pharmacology

 

Seth I. Berger and Ravi Iyengar

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2752618/pdf/btp465.pdf

 

 

Biological Networks: The Tinkerer as an Engineer

U Alon

 

http://dp.univr.it/~laudanna/Systems%20Biology/Publications/Reviews/Network%20analysis/Biological%20Networks%20The%20Tinkerer%20as%20an%20Engineer.pdf

 

 

Cell Biology: Networks, Regulation and Pathways

GAŠPER TKACˇ IK , WILLIAM BIALEK

 

https://www.princeton.edu/~wbialek/our_papers/tkacik+bialek_09b.pdf

 

 

 

Coupling oscillations and switches in genetic networks

Didier Gonze

 

https://pdfs.semanticscholar.org/0878/d29052b34bc3fe43649c826fd9fd0506e445.pdf

 

 

 

Biological Oscillators and Switches

 

http://faculty.washington.edu/hqian/amath4-523/Murray-Math-Biol-ch7.pdf

 

 

 

Design principles of biological oscillators

 

Didier Gonze

 Nonlinear Chemical Dynamics: Oscillations, Patterns, and Chaos

 

Irving R. Epstein

Kenneth Showalter

 

 

Modelling biological oscillations

 

Shan He

 

A comparative analysis of synthetic genetic oscillators

 

Oliver Purcell1,*, Nigel J. Savery3, Claire S. Grierson4 and Mario di Bernardo2,5

 

Hierarchy Theory in Biology, Ecology and Evolution

Hierarchy Theory in Biology, Ecology and Evolution

 

I have always been intrigued by multi-level thinking whether it is in organizations, biology, ecology, and evolutionary theory.

  • Plant – Division – Corporate – Industry – Macro-economy
  • Molecules – Organelles – Cells – Tissue – Organs – Whole body
  • Organism – Populations – Communities – Ecosystem –  Bio-Sphere

 

How does human body forms from Molecules?  Is it all evolutionary?  or is there a role for Vitalism?

How to integrate decision making in organizations at multi levels?  From Corporate level to Plant Level.

How does an Individual fits in Groups, Communities, Society, and Ecosystem?

What is the role of fractals thinking in Evolutionary Biology?

 

A SUMMARY OF THE PRINCIPLES OF HIERARCHY THEORY

The Hierarchy theory is a dialect of general systems theory. It has emerged as part of a movement toward a general science of complexity. Rooted in the work of economist, Herbert Simon, chemist, Ilya Prigogine, and psychologist, Jean Piaget, hierarchy theory focuses upon levels of organization and issues of scale. There is significant emphasis upon the observer in the system.

Hierarchies occur in social systems, biological structures, and in the biological taxonomies. Since scholars and laypersons use hierarchy and hierarchical concepts commonly, it would seem reasonable to have a theory of hierarchies. Hierarchy theory uses a relatively small set of principles to keep track of the complex structure and a behavior of systems with multiple levels. A set of definitions and principles follows immediately:

Hierarchy: in mathematical terms, it is a partially ordered set. In less austere terms, a hierarchy is a collection of parts with ordered asymmetric relationships inside a whole. That is to say, upper levels are above lower levels, and the relationship upwards is asymmetric with the relationships downwards.

Hierarchical levels: levels are populated by entities whose properties characterize the level in question. A given entity may belong to any number of levels, depending on the criteria used to link levels above and below. For example, an individual human being may be a member of the level i) human, ii) primate, iii) organism or iv) host of a parasite, depending on the relationship of the level in question to those above and below.

Level of organization: this type of level fits into its hierarchy by virtue of set of definitions that lock the level in question to those above and below. For example, a biological population level is an aggregate of entities from the organism level of organization, but it is only so by definition. There is no particular scale involved in the population level of organization, in that some organisms are larger than some populations, as in the case of skin parasites.

Level of observation: this type of level fits into its hierarchy by virtue of relative scaling considerations. For example, the host of a skin parasite represents the context for the population of parasites; it is a landscape, even though the host may be seen as belonging to a level of organization, organism, that is lower than the collection of parasites, a population.

The criterion for observation: when a system is observed, there are two separate considerations. One is the spatiotemporal scale at which the observations are made. The other is the criterion for observation, which defines the system in the foreground away from all the rest in the background. The criterion for observation uses the types of parts and their relationships to each other to characterize the system in the foreground. If criteria for observation are linked together in an asymmetric fashion, then the criteria lead to levels of organization. Otherwise, criteria for observation merely generate isolated classes.

The ordering of levels: there are several criteria whereby other levels reside above lower levels. These criteria often run in parallel, but sometimes only one or a few of them apply. Upper levels are above lower levels by virtue of: 1) being the context of, 2) offering constraint to, 3) behaving more slowly at a lower frequency than, 4) being populated by entities with greater integrity and higher bond strength than, and 5), containing and being made of – lower levels.

Nested and non-nested hierarchies: nested hierarchies involve levels which consist of, and contain, lower levels. Non-nested hierarchies are more general in that the requirement of containment of lower levels is relaxed. For example, an army consists of a collection of soldiers and is made up of them. Thus an army is a nested hierarchy. On the other hand, the general at the top of a military command does not consist of his soldiers and so the military command is a non-nested hierarchy with regard to the soldiers in the army. Pecking orders and a food chains are also non-nested hierarchies.

Duality in hierarchies: the dualism in hierarchies appears to come from a set of complementarities that line up with: observer-observed, process-structure, rate-dependent versus rate-independent, and part-whole. Arthur Koestler in his “Ghost in The Machine” referred to the notion of holon, which means an entity in a hierarchy that is at once a whole and at the same time a part. Thus a holon at once operates as a quasi-autonomous whole that integrates its parts, while working to integrate itself into an upper level purpose or role. The lower level answers the question “How?” and the upper level answers the question, “So what?”

Constraint versus possibilities: when one looks at a system there are two separate reasons behind what one sees. First, it is not possible to see something if the parts of the system cannot do what is required of them to achieve the arrangement in the whole. These are the limits of physical possibility. The limits of possibility come from lower levels in the hierarchy. The second entirely separate reason for what one sees is to do with what is allowed by the upper level constraints. An example here would be that mammals have five digits. There is no physical reason for mammals having five digits on their hands and feet, because it comes not from physical limits, but from the constraints of having a mammal heritage. Any number of the digits is possible within the physical limits, but in mammals only five digits are allowed by the biological constraints. Constraints come from above, while the limits as to what is possible come from below. The concept of hierarchy becomes confused unless one makes the distinction between limits from below and limits from above. The distinction between mechanisms below and purposes above turn on the issue of constraint versus possibility. Forget the distinction, and biology becomes pointlessly confused, impossibly complicated chemistry, while chemistry becomes unwieldy physics.

Complexity and self-simplification: Howard Pattee has identified that as a system becomes more elaborately hierarchical its behavior becomes simple. The reason is that, with the emergence of intermediate levels, the lowest level entities become constrained to be far from equilibrium. As a result, the lowest level entities lose degrees of freedom and are held against the upper level constraint to give constant behavior. Deep hierarchical structure indicates elaborate organization, and deep hierarchies are often considered as complex systems by virtue of hierarchical depth.

Complexity versus complicatedness: a hierarchical structure with a large number of lowest level entities, but with simple organization, offers a low flat hierarchy that is complicated rather than complex. The behavior of structurally complicated systems is behaviorally elaborate and so complicated, whereas the behavior of deep hierarchically complex systems is simple.

Hierarchy theory is as much as anything a theory of observation. It has been significantly operationalized in ecology, but has been applied relatively infrequently outside that science. There is a negative reaction to hierarchy theory in the social sciences, by virtue of implications of rigid autocratic systems or authority. When applied in a more general fashion, even liberal and non-authoritarian systems can be described effectively in hierarchical terms. There is a politically correct set of labels that avoid the word hierarchy, but they unnecessarily introduce jargon into a field that has enough special vocabulary as it is.

A SHORT ANNOTATED BIBLIOGRAPHY OF HIERARCHY THEORY.

This bibliography is in chronological order, so that the reader can identify the early classics as opposed to the later refinements. If you must choose just one book to read, turn to the last reference in this bibliography, Ahl and Allen, 1996. Simon, H.. A. 1962. The architecture of complexity. Proceedings of the American philosophical society 106: 467-82. This is the foundation paper of hierarchy theory originating from an economist. It was a re-published in “Sciences of the Artificial” by Simon. It introduces the idea of near-decomposability. If systems were completely decomposable, then there would be no emergent whole, because the parts would exist only separately. The “near” in near-decomposable allows the upper level to emerge from the fact that the parts anre not completely separate.

Koestler, Arthur. 1967. The ghost in the machine. Macmillan, New York. This is a long hard look at human social structure in hierarchical terms. The notion of holon first occurs in this work. This is a classic work, but is easily accessible to the lay public.

Whyte, L.. L.., A. G. Wilson and D. Wilson (eds.). 1969. Hierarchical structures. American Elsevier, New York. This is a classic collection of early scholarly works by some of the founders of hierarchical thinking.

Pattee, H.. H. (ed.) 1973. Hierarchy theory: the challenge or complex systems. Braziller, New York. This edited volume has some classic articles by Pattee, Simon and others.

Allen, T. F. H. and T. B. Starr. 1982. Hierarchy: perspectives for ecological complexity. University Chicago Press. This book has a significant ecological component but is much more generally about hierarchical structure. It is abstract and a somewhat technical treatment but has been the foundation work for the application of hierarchy theory in ecology and complex systems theory at large.

Salthe, S. 1985. Evolving Hierarchical Systems: their structure and representation. Columbia University Press, New York. This book has a strong structural bias, in contrast to the process oriented approach of Allen and the other ecologists in this bibliography. Salthe introduces the notion of the Triadic, where there is a focus on 1) the system as both a whole above the levels below and 2) a part belonging to another level above, 3) not forgetting the level of the structure itself in between. While much biological hierarchy theory takes an anti-realist point view, or is at least reality-agnostic, wherein the ultimate reality of hierarchical arrangement is left moot, Salthe’s version of hierarchy theory is concerned with the ultimate reality of structure. The anti-realist view of structure is that it is imposed by the observer, and may or may not correspond to any ultimate reality. If structure does correspond to ultimate, external reality, we could never know that to be so. Salthe’s logic is consistent but always takes a structural and ontological position.

O’Neill, R. V., D. DeAngelis, J. Waide and T. F. H. Allen. 1986. A hierarchical concept of ecosystems. Princeton University Press. This is a distinctly ecological application of hierarchy theory, making the critical distinction between process functional ecosystem approaches as opposed to population and community relationships. It is an application of hierarchy theory to ecosystem analysis.

Allen T. F. H. and T. Hoekstra. 1992. Toward a unified ecology. Columbia University Press. This book turns on hierarchy theory, but is principally a book about ecology. It goes beyond the O’Neill et al book, in that it makes the distinction between many types of ecology (landscape, ecosystem, community, organism, population, and biomes) on the one hand, and scale of ecology on the other hand. It ends with practical applications of hierarchy theory and ecological management.

Ahl, V. and T. F. H. Allen. 1996. Hierarchy theory, a vision, vocabulary and epistemology. Columbia University Press. This slim a volume is an interdisciplinary account of a hierarchy theory, and represents the shallow end of the pool. It is the primer version of Allen and Starr 1982. It is full of graphical images to ease the reader into a hierarchical perspective. It makes the distinction between levels of organization and levels of observation. It takes a moderate anti-realist point of view, wherein there may be an external reality, but it is not relevant to the discourse. We only have access to experience, which must of necessity involve observer values and subjectivity. There are examples from a wide discussion of many disciplines. Included are examples from psychology, ecology, the law, political systems and philosophy. It makes reference to the global and technological problems facing humanity, and offers hierarchy theory as one tool in the struggle. The summary of hierarchy theory in the opening paragraphs above comes from this book.

This summary was compiled by

Timothy F. Allen, Professor of Botany,
University of Wisconsin Madison,
Madison Wisconsin 53706 — 1381.
Email – tfallen@facstaff.wisc.edu

 

 

Key People:

  • James Grier Miller
  • Howard Pattee
  • Stanley Salthe
  • T F Allen
  • Herbert Simon
  • NILES ELDREDGE
  • CS Holling

 

 

Key Sources of Research:

 

A SUMMARY OF THE PRINCIPLES OF HIERARCHY THEORY

T Allen

http://www.isss.org/hierarchy.htm

http://www.botany.wisc.edu/allenlab/AllenLab/Hierarchy.html

 

 

Hierarchy Theory

Paweł Leśniewski

 

http://www.uni-kiel.de/ecology/users/fmueller/salzau2006/ea_presentations/Data/2006-06-28_-_Hierarchy_Theory.pdf

 

 

Summary of the Principles of Hierarchy Theory

S.N. Salthe

 

http://www.nbi.dk/~natphil/salthe/Summary_of_the_Principles_o.pdf

 

 

HOWARD PATTEE’S THEORETICAL BIOLOGY:

A RADICAL EPISTEMOLOGICAL STANCE TO APPROACH LIFE, EVOLUTION ANDCOMPLEXITY.

Jon Umerez

 

http://www.informatics.indiana.edu/rocha/publications/pattee/umerez.pdf

 

 

 

Hierarchy Theory as the Formal Basis of Evolutionary Theory

 

http://www.bbk.ac.uk/tpru/StephenWood/Publications/HierarchyTheoryastheFormalBasisofEvolutionaryTheory.pdf

 

 

The Concept of Levels of Organization in the Biological Sciences

 

PhD Thesis Submitted August 2014 Revised June 2015

Daniel Stephen Brooks

 

http://d-nb.info/1082033960/34

 

 

A spatially explicit hierarchical approach to modeling complex ecological systems: theory and applications

Jianguo Wu , John L. David

 

http://leml.asu.edu/jingle/Web_Pages/Wu_Pubs/PDF_Files/Wu_David_2002.PDF

 

 

What is the Hierarchy Theory of Evolution?

 

http://hierarchygroup.com/wp-content/uploads/2014/07/What-Is-The-Hierarchy-Theory.pdf

 

 

HIERARCHICAL ORGANIZATION OF ECOSYSTEMS

Jackson R. Webster

 

http://coweeta.uga.edu/publications/274.pdf

 

 

Ecological hierarchies and self-organisation – Pattern analysis, modelling and process integration across scales

Hauke Reutera,, Fred Jopp, José M. Blanco-Morenod, Christian Damgaarde, Yiannis Matsinosf, Donald L. DeAngelis

 

http://izt.ciens.ucv.ve/ecologia/Archivos/ECO_POB%202010/ECOPO1_2010/Reuter_etal_BAAE%202010.pdf

 

 

Levels of organization in biology: on the nature and nomenclature of ecology’s fourth level

William Z. Lidicker, Jr

 

http://www.uff.br/ecosed/Artigo4.pdf

 

 

Chapter 24

Hierarchy Theory: An Overview

Jianguo Wu

 

http://izt.ciens.ucv.ve/ecologia/Archivos/ECO_POB%202016/ECOPO7_2016/Jorgensen%20et%20al%202016.pdf

 

 

Heterarchies: Reconciling Networks and Hierarchies

Graeme S. Cumming

https://www.researchgate.net/publication/303508940_Heterarchies_Reconciling_Networks_and_Hierarchies

 

 

Evolutionary Theory

A HIERARCHICAL PERSPECTIVE

EDITED BY NILES ELDREDGE, TELMO PIEVANI, EMANUELE SERRELLI, AND ILYA TEMKIN

 

 

Holons, creaons, genons, environs, in hierarchy theory: Where we have gone

Timothy Allen, Mario Giampietro

http://www.sciencedirect.com/science/article/pii/S0304380014002993

 

 

The Evolutionary Foundations of Hierarchy: Status, Dominance, Prestige, and Leadership

Mark van Vugt & Joshua M. Tybur

http://www.professormarkvanvugt.com/images/files/Handbook_of_Evolutionary_Psychologymvv2014rev.pdf

 

 

The Microfoundations of Macroeconomics: An Evolutionary Perspective

Jeroen C.J.M. van den Bergh

John M. Gowdy

 

https://papers.tinbergen.nl/00021.pdf

 

 

Understanding the complexity of Economic, Ecological, and Social Systems

C S Holling

http://www.esf.edu/cue/documents/Holling_Complexity-EconEcol-SocialSys_2001.pdf

 

 

Hierarchical Structures

Stanley N. Salthe

 

https://www.researchgate.net/profile/Salthe_Stanley/publication/257522907_Hierarchical_Structures/links/5768411408ae7f0756a2248c.pdf

 

 

Two Frameworks for Complexity Generation in Biological Systems

Stanley N. Salthe

 

http://www.nbi.dk/natphil/salthe/A-life_Conf_paper_Word.pdf

http://www.nbi.dk/~natphil/salthe/_publ_classified_by_topic.pdf

 

 

Spatial scaling in ecology

J. A. WIENS

 

http://www.functionalecology.org/SpringboardWebApp/userfiles/fec/file/Spatial%20scaling%20in%20ecology%20v3%20n4.pdf

 

 

The Spirit of Evolution

by Roger Walsh

An overview of Ken Wilber’s book Sex, Ecology, Spirituality: The Spirit of Evolution (Shambhala, 1995).

http://cogweb.ucla.edu/CogSci/Walsh_on_Wilber_95.html

Bank of Finland’s Payment And Settlement System Simulator (BoF-PSS2)

Bank of Finland’s Payment And Settlement System Simulator (BoF-PSS2)

 

From Payment and Settlement System Simulator

BOF-PSS2

The Bank of Finland provides a simulator called BoF-PSS2 for replicating payment and securities settlement systems. The simulator is adaptable for modelling multisystem setups that can be a combination of payment, securities settlement systems and CCP’s. The simulator is known to be unique and the first of its kind. Since its launch in 2002 it has been distributed to more than 90 countries and has contributed to numerous studies and research papers.

The simulator can be used to fulfill some of the regulatory requirements stated in the PFMI’s and BCBS requirements such as identifying the liquidity risks inpayment systems. Here under are topics the simulator can be used for:

  • Settlement, liquidity and credit risks in FMI’s
  • Systemic Risks and Counterparty risks in FMI’s
  • Identification of critical counterparts
  • Policy change impact evaluation
  • Network analysis
  • Liquidity dependency analysis
  • Relationship analysis of Monetary policy and liquidity needs for settlement of payments
  • Evaluation of sufficiency of liquidity buffers and margins
  • System merger effects on liquidity needs
  • System performance benchmarking
  • Netting algorithm testing and development
  • System development and prototyping

In comparison to static calculations of indicators, the simulation results naturally incorporate network (or systemic) effects rising from the payments flows and the technical properties of the infrastructures themselves. The results obtained from simulations are directly interpretable and have a self-evident meaning which is not always the case with all indicators. The results can directly be used for risk management purposes for example when evaluating the sufficiency of liquidity buffers and margins. Computer simulations take advantage of using the available information in full without losing micro-level information due to indicator aggregations.

The simulator is freely available for research purposes, and has already been introduced in numerous countries. It is possible to tailor and adapt the simulator to specific payment systems. Several adaptations of the simulator have already been made, eg. for TARGET2. The simulator team provides trainings, consultation and tailored adaptations which are priced for cost recovery. The training course aims at providing necessary skills for efficient use of BoF-PSS2 with hands on computer class exercises. It also presents numerous examples from real studies where the tool has been used. For more details see the training course outline. Minimum attendance to the session is four participants.

Basically, trainings are organised upon demand and it is also possible to order a training course to be held onsite outside the proposed dates.

 

From Payment and Settlement System Simulator / Product Page

product_en_144ppi

From Payment and Settlement System Simulator / Documentation page

The Bank of Finland Payment and Settlement System Simulator, version 2 (BoF-PSS2), is a powerful tool for payment and securities settlement system simulations. The simulator supports multiple system structures and various settlement models.

The simulator is designed for analysing liquidity needs and risks in payment and settlement systems. Special situations, often difficult or impossible to test in a real environment, can be readily simulated with BoF-PSS2. Thus, users can study how behavioral patterns and changes in policy and conventions impact the payment and settlement systems and participants. The efficiency of gridlock-resolution and liquidity-saving measures can be analyzed as well.

The application is divided into three sub-systems:

  • Input sub-system for preparing and defining the input data,
  • Execution sub-system for running simulations,
  • Output sub-system for basic analyses of simulation results.

Different settlement logics are implemented into separate algorithms. To replicate specific systems, appropriate algorithms must be selected with appropriate parameters. Different algorithm combinations can be used to replicate a large number of current and potential settlement conventions and structures. Real-time gross settlement systems (RTGS), continuous net settlement systems (CNS), deferred net settlement systems (DNS) and hybrid systems can be implemented with the simulator as well as securities settlement and multicurrency systems. Inter-system connections and bridges make it possible to define multi- system environments consisting of various types of interdependent systems. E.g. it is possible to replicate the interaction of RTGS and securities settlement systems.

Advanced users of BoF-PSS2 can define and build their own user modules/algorithms and expand the basic features of the simulator to analyse new types of settlement processes. It is also possible to implement agent based modeling by adding algorithms replicating the participants’ behavior and decision making to control and alter the flow of submitted transactions. As a later addition, the simulator also has a network analysis module for generating networks and network indicators from either input data or results of simulations.

BoF-PSS2 has an easy to use graphical user interface. It is also possible to automate the use of the simulator via its command line interface (CLI).

 

From Payment and Settlement System Simulator / Product Page

TARGET2 SIMULATOR

A separate TARGET2 simulator version of BoF-PSS2 has been developed and delivered for the European System of Central Banks. It is based on the same basic software architechture and features of BoF-PSS2. Additional features are implemented as separate algorithm modules which replicate the proprietary algorithms of actual TARGET2 system. It is used by Eurosystem for quantitative analyses and numerical simulations of TARGET2.

TARGET2 simulator has been jointly delivered by Suomen Pankki (Bank of Finland) and the 3CB (Banca d’Italia, Deutsche Bundesbank, Banque de France) based on a decision of ECB Governing Council.

 

 

Key Terms

  • Liquidity Simulator
  • Payment System
  • Risk Management
  • Financial Stability
  • Cascades of Failures
  • Congestions and Delays
  • Financial Market Infrastructures
  • Payment Networks
  • Contagion
  • RTGS
  • Simulation Analysis
  • TARGET2
  • Intraday Payments

 

Key People

  • Harry Leinonen
  • Tatu Laine
  • Matti Hellqvist
  • Kimmo Soramäki

 

 

Key Sources of Research:

 

Payment and Settlement System Simulator – A tool for analysis of liquidity, risk and efficiency

Bank of Finland Payment and Settlement Simulator

2006

 

https://www.suomenpankki.fi/globalassets/en/financial-stability/payment-and-settelement-system-simulator/events/2006_11a_hl.pdf

 

 

BoF-PSS2 Technical structure and simulation features

Harry Leinonen

https://www.suomenpankki.fi/globalassets/en/financial-stability/payment-and-settelement-system-simulator/events/20031519seminarpresentationleinonen2.pdf

 

 

Payment and Settlement System Simulator

https://www.suomenpankki.fi/en/financial-stability/bof-pss2-simulator/

https://www.suomenpankki.fi/en/financial-stability/bof-pss2-simulator/product/

https://www.suomenpankki.fi/en/financial-stability/bof-pss2-simulator/events/

 

 

Publications

https://www.suomenpankki.fi/en/financial-stability/bof-pss2-simulator/publications/

 

 

Quantitative analysis of financial market infrastructures: further perspectives on financial stability

E50

https://helda.helsinki.fi/bof/handle/123456789/13990

 

 

Diagnostics for the financial markets : computational studies of payment system : Simulator Seminar Proceedings 2009-2011

E45

https://helda.helsinki.fi/bof/handle/123456789/9381

 

 

Simulation analyses and stress testing of payment networks

E42

https://helda.helsinki.fi/bof/handle/123456789/9369

 

 

Simulation studies of liquidity needs, risks and efficiency in payment networks : Proceedings from the Bank of Finland Payment and Settlement System Seminars 2005-2006

E39

https://helda.helsinki.fi/bof/handle/123456789/9370

 

 

Liquidity, risks and speed in payment and settlement systems : a simulation approach

E31

https://helda.helsinki.fi/bof/handle/123456789/9355

 

 

Simulation Analysis and Tools for the Oversight of Payment Systems

 

http://www.cemla.org/actividades/2012/2012-12-payments/2012-12-vigilanciasistemasdepago-10.pdf

 

 

Utilizing the BoF simulator in quantitative FMI analysis

Tatu Laine

Banco de México

15.10.2014

 

http://www.banxico.org.mx/publicaciones-y-discursos/publicaciones/seminarios/banco-de-mexico_-the-evolving-landscape-of-payment/%7B15D9D1D3-D455-1E98-6FA6-AFB3B30C4ACB%7D.pdf

 

 

TARGET2 Simulator

https://www.banque-france.fr/sites/default/files/media/2016/11/07/target_newsletter_7_2013.pdf

 

 

Intraday patterns and timing of TARGET2 interbank payments

Marco Massarenti

Silvio Petriconi

Johannes Lindner

 

https://pdfs.semanticscholar.org/7177/0b5a0eb557b478843891449221c6ed2e7502.pdf

 

 

Communities and driver nodes in the TARGET2 payment system

Marco Galbiatiy, Lucian Stanciu-Vizeteuz

June 17, 2015

 

https://www.researchgate.net/profile/Marco_Galbiati/publication/279511583_Communities_and_driver_nodes_in_the_TARGET2_payment_system/links/5593d39c08ae1e9cb42a1904.pdf

 

 

Payment Delays and Contagion

Ben Craig† Dilyara Salakhova‡ Martin Saldias§

November 14, 2014

http://www.systemic-risk-hub.org/papers/bibliography/CraigSalakhovaSaldias_2014_preview.pdf

 

 

Federal Reserve Bank of New York Economic Policy Review

September 2008 Volume 14 Number 2

Special Issue: The Economics of Payments

 

https://www.newyorkfed.org/medialibrary/media/research/epr/2008/EPRvol14n2.pdf

 

 

Contagion in Payment and Settlement Systems

 

Matti Hellqvist

2006

 

https://www.imf.org/external/np/seminars/eng/2006/stress/pdf/mh.pdf

 

 

Applications of BoF-PSS2 simulator and how to use it in agent based models

 

http://terna.to.it/ABM-BaF09/presentations/Hellqvist(presentation)_ABM-BaF09.pdf

 

 

Simulation and Analysis of Cascading Failure in Critical Infrastructure

Robert Glass, Walt Beyeler, Kimmo Soramäki, MortenBech and Jeffrey Arnold

Sandia National Laboratories, European Central Bank,  Federal Reserve Bank of New York

https://www.suomenpankki.fi/globalassets/en/financial-stability/payment-and-settelement-system-simulator/events/07-glass_pres.pdf

 

 

Simulation analysis of payment systems

 

Kimmo Soramäki

2011

http://www.cemla.org/actividades/2011/2011-11-vigilancia/2011-11-vigilancia-07.pdf

 

 

Simulating interbank payment and securities settlement mechanisms with the BoF-PSS2 simulator

Harry Leinonen

Kimmo Soramäki

 

2003

 

https://www.suomenpankki.fi/globalassets/en/rahoitusjarjestelman_vakaus/bof-pss2/documentation/bof_dp_2303.pdf

 

On Anticipation: Going Beyond Forecasts and Scenarios

On Anticipation: Going Beyond Forecasts and Scenarios

 

From Anticipation.Info of Mihai Nadin

A Second Cartesian Revolution

For about 400 years, humankind, or at least the western world, has let itself be guided by the foundation set by Descartes and Newton. The cause-and-effect, deterministic model of the machine became so powerful that every thing and every being came to be considered a machine. As a description of the material world and as an expression of the laws governing its functioning, deterministic-based physics and Cartesian reductionism (of the whole to its parts) proved to be extremely powerful instruments in the overall progress of humankind. But neither Descartes nor Newton, nor most of their followers, could have envisioned the spectacular development of science in its current depth and breadth.

The physicist Erwin Schrödinger concluded that organisms are subject to “a new physics,” which he did not produce, but rather viewed as necessary. This new physics might well be the domain of anticipation. Indeed, from within physics itself—that is, quantum mechanics—a possible understanding of some aspects of anticipation can be derived.

The realization that the world is the unity of reaction and anticipation is not new. What is new is the awareness of the limits of our understanding a dynamics of change that transcends the deterministic view. The urgent need for such an understanding is probably best expressed in the spectacular development of the life sciences.

The perspective of the world that anticipation opens justifies the descriptor “a second Cartesian Revolution.” Instead of explaining complexity away, we will have to integrate it into our existence as the informational substratum of rich forms through which anticipatory processes take place.

 

From Anticipation.Info of Mihai Nadin

Anticipation: Why is it a subject of research?

Anticipation occurs in all spheres of life. It complements the physics of reaction with the pro-active quality of the living. Nature evolves in a continuous anticipatory fashion targeted at survival. The dynamics of stem cells demonstrate this mechanism. Through entailment from a basic stem cell an infinite variety of biological expression becomes possible.

Sometimes we humans are aware of anticipation, as when we plan. Often, we are not aware of it, as when processesembedded in our body and mind take place before we realize their finality. In tennis, for example, the return of a professional serve can be successful only through anticipatory mechanisms. A conscious reaction takes too long to process. Anticipation is the engine driving the stock market. Creativity in art and design are fired by anticipation.

“The end is where we start from,” T. S. Eliot once wrote. Before the archer draws his bow, his mind has already hit the target. Motivation mechanisms in learning, the arts, and all types of research are dominated by the underlying principle that a future state—the result—controls present action, aimed at success. The entire subject of prevention entails anticipatory mechanisms.

 

From Anticipation.Info of Mihai Nadin

Research into anticipation revealed various aspects that suggested a number of definitions.

Robert Rosen, Mihai Nadin, Daniel Dennett and others who approached particular aspects of anticipation contributed to some of these definitions. Mihai Nadin (cf. Anticipation – A Spooky Computation) attempted an overview of the various angles from which anticipation can be approached if the focus is on computation. This overview is continued and expanded in the integrated publication (book+dvd+website) to which this website belongs. The following 12 definitions, or descriptions, of anticipation should be understood as working hypotheses. It is hoped and expected that the knowledge community of those interested in anticipation will eventually refine these definitions and suggest new ones in order to facilitate a better understanding of what anticipation is and its importance for the survival of living systems.

  • An anticipatory system is a system whose current state is determined by a future state. “The cause lies in the future,”. (cf. Robert Rosen, Heinz von Foerster)
  • Anticipation is the generation of a multitude of dynamic models of human actions and the resolution of their conflict. (cf. Mihai Nadin)
  • An anticipatory system is a system containing a predictive model of itself and/or of its environment that allows it to change state at an instant in accord with the model’s predictions pertaining to a later instant. (cf. Robert Rosen)
  • Anticipation is a process of co-relation among factors pertaining to the present, past and future of a system. (cf. Mihai Nadin)
  • Anticipation is an expression of the connectedness of the world, in particular of quantum non-locality. (cf. Mihai Nadin)
  • Anticipation is the expression of natural entailment. (cf. Robert Rosen)
  • Anticipation is a mechanism of synchronization and integration. (cf. Mihai Nadin)
  • Anticipation is an attractor within dynamic systems. (cf. Mihai Nadin)
  • Anticipation is a recursive process described through the functioning of a mechanism whose past, present, and future states allow it to evolve from an initial to a final state that is implicitly embedded in the mechanism. (cf. Mihai Nadin)
  • Anticipation is a realization within the domain of possibilities. (cf. Mihai Nadin)
  • Anticipatory mechanisms can be reinforced through feedback. Feedforward and inverse kinetics are part of the integrated mechanism of anticipation. (cf. Daniel Dennett, Daniel Wolpert, Nadin)
  • Anticipation is a power law-based long-range interaction. (cf. Mihai Nadin)

 

From An Introduction to the Ontology of Anticipation

Recent years have witnessed the growth of significant interest in theories and methodologies which seek to foresee the future development of relevant situations. Studies of the future fall under many different denominations, and they employ a huge variety of techniques, ranging from forecasting to simulation, from planning to trend extrapolation, from future studies and scenarios to anticipatory systems. Widely different conceptualisations and formalisations have been proposed as well.1 This remarkable variety may be partly simplified by making explicit the main underlying assumptions of at least some of them. Two of these assumptions are that (1) the future is at least partly governed by the past, and (2) the future can be better confronted by opening our minds and learning to consider different viewpoints. According to (1) the future is part of a structured story whose past and present are at least partially known. The claim is defended that the forces that have shaped past and present situations will still be valid while the situation under consideration unfolds. The core thesis is that the future is embedded in the past; it is the projection of the past through the present. Time series analysis, trend extrapolation, and forecasting pertain to this family. Any of the mentioned methodologies may be further supplemented by computer-based simulations. On the other hand, instead of directly addressing the problem of searching for the seeds of the future in the past, (2) considers the different problem of preparing for the unforeseeable novelties awaiting us in the future. Learning about widely different outcomes is now the issue: one must be ready to consider and address possibly unfamiliar or alien scenarios. The main outcome of this exercise is an increased capacity to distinguish among possible, probable, and preferred future scenarios. These activities come under the heading of future studies, while scenario construction is the best known methodology adopted by practitioners. For now on I shall refer to (1) and (2) as respectively the forecasting and the scenario viewpoints. Forecasts and scenarios are not contradictory one to the other. They may and usually do coexist, since they address the future from two different standpoints. Furthermore, experience shows that both are useful. This paper introduces a third, different viewpoint, here termed the viewpoint of anticipatory systems, which can be profitably synthesized with forecasts and scenarios; i.e. it is not contradictory with the claims of either the forecasting or scenario viewpoint. Recent years have witnessed the growth of significant interest in anticipation.2 Anticipatory theories have been proposed in fields as different as physics, biology, physiology, neurobiology, psychology, sociology, economy, political science, computer science and philosophy. Unfortunately, no systematic comparison among the different viewpoints has so far been developed. It is therefore fair to claim that currently no general theory of anticipation is available. Generally speaking, anticipation concerns the capacity exhibited by some systems to tune their behaviour according to a model of the future evolution of the environment in which they are embedded. Generally speaking, the thesis is defended that “An anticipatory system is a system containing a predictive model of itself and/or its enviroment, which allows it to change state at an instant in accord with the model‟s predictions pertaining to a later instant” (Rosen [19: 341]). The main difference between forecasting and scenarios on the one hand, and anticipation on the 1 See, among many others, Adam [1], Bell [4], Cornish [5], Godet [7], Lindgren and Bandhold [8], Retzbach [16], Slaughter [22], Woodgate and Pethrick [23]. 2 Starting from the seminal Rosen [19]. See also [20], [21]. 2 other, is that the latter is a property of the system, intrinsic to its functioning, while the former are cognitive strategies that a system A develops in order to understand the future of some other system B (of which A may or may not be a component element).

 

 

Key Terms

  • Hyper Sets
  • Hyper Incursion
  • Hyper Recursion
  • Recursion
  • Incursion
  • Anticipatory Systems
  • Weak Anticipation
  • Strong Anticipation

 

Key People

  • Roberto Poli
  • Mihai Nadin
  • Riel Miller
  • Robert Rosen
  • John J Kineman
  • Daniel M Dubois
  • John Collier
  • Loet Leydesdorff

 

 

Key Sources of Research:

 

Systems and models with anticipation in physics and its applications

A Makarenko

http://iopscience.iop.org/article/10.1088/1742-6596/394/1/012024/pdf

 

 

Anticipatory Viable Systems

Maurice Yolles

Daniel Dubois

 

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.195.2167&rep=rep1&type=pdf

https://pdfs.semanticscholar.org/ab7b/92666ab431a3f68df0ce8139d594aaeb3f87.pdf

 

 

Anticipatory Kaldor-Kalecki Model of Business Cycle

Daniel M. Dubois

 

https://www2.gwu.edu/~rpsol/conf2004/emcsr2004_Daniel-Dubois.pdf

 

 

An Introduction to the Ontology of Anticipation

Roberto Poli

 

http://cspo.org/wp-content/uploads/2014/11/read_Poli-An-Introduction-to-the-Ontology-of-Anticipation.pdf

 

 

Towards an anticipatory view of design

Theodore Zamenopoulos and Katerina Alexiou

 

http://www.ida.liu.se/divisions/hcs/ixs/material/DesResMeth09/Theory/anticipation.pdf

 

 

The role of anticipation in cognition

Alexander Riegler

http://www.univie.ac.at/constructivism/people/riegler/pub/Riegler%20A.%20(2001)%20The%20role%20of%20anticipation%20in%20cognition.pdf

https://pdfs.semanticscholar.org/db82/7d5ded82973e081a572c79bd76f8188b0ed5.pdf

 

 

SDA: System Dynamics Simulation of Inter Regional Risk Management

Using a Multi-Layered Model with Delays and Anticipation

Daniel M Dubois1, Stig C Holmberg

2012

 

https://www.systemdynamics.org/conferences/2012/proceed/papers/P1374.pdf

 

 

Anticipatory Modeling and Simulation for Inter Regional Security

Daniel M. Dubois, Viveca Asproth, Stig C. Holmberg

Ulrica Löfstedt, and Lena-Maria Öberg

 

http://orbi.ulg.be/bitstream/2268/109076/1/dubois-C-EMCSR-2012.pdf

 

 

Attentional and Semantic Anticipations in Recurrent Neural Networks

Frédéric Lavigne1 and Sylvain Denis

 

http://cogprints.org/2249/3/lavigne-denis-2001.pdf

 

 

Not Everything We Know We Learned

Mihai Nadin

 

http://www.nadin.name/index.html?/publications/articles_b0.html

 

 

Anticipation in the Constructivist Theory of Cognition

Ernst von Glasersfeld

 

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.8.1971&rep=rep1&type=pdf

 

 

The Communication of Meaning in Anticipatory Systems: A Simulation Study of the Dynamics of Intentionality in Social Interactions

Loet Leydesdorff

https://arxiv.org/pdf/0911.1448.pdf

 

 

Information Systems and the Theory of Categories: Is Every Model an Anticipatory System?

M. A. Heather, B. N. Rossiter

 

http://nrl.northumbria.ac.uk/3732/1/Rossiter_Information%20systems%20and%20the%20theory%20of%20categories.pdf

 

 

Anticipation.Info of Mihai Nadin

http://www.anticipation.info

http://www.nadin.name/index.html?/publications/articles_b0.html

 

 

Institute for Research in Anticipatory Systems

http://www.anteinstitute.org

 

 

Robert Rosen’s anticipatory systems

A.H. Louie

 

https://www.researchgate.net/profile/A_Louie/publication/228091658_Robert_Rosen’s_anticipatory_systems/links/09e4150cdd961e4a87000000.pdf

 

 

Computing Anticipatory Systems with Incursion and Hyperincursion

Daniel M. DUBOIS

https://www.researchgate.net/profile/Daniel_Dubois2/publication/228596416_Computing_anticipatory_systems_with_incursion_and_hyperincursion/links/559558fe08ae99aa62c720f3.pdf

 

 

Anticipatory Systems: Philosphical Methematical and Methodological Foundations.

Rosen R.

Springer; 2014.

 

 

ROBERT ROSEN’S ANTICIPATORY SYSTEMS THEORY: THE ART AND SCIENCE OF THINKING AHEAD

Judith Rosen

 

http://journals.isss.org/index.php/proceedings53rd/article/viewFile/1249/410

 

 

The Many Aspects of Anticipation

Roberto Poli

University of Trento

https://pdfs.semanticscholar.org/b63f/9b480ac8cd96999f281892caba100baacc79.pdf

 

 

Being Without Existing: The Futures Community at a Turning Point? A Comment on Jay Ogilvy’s “Facing the Fold”

By Riel Miller

https://www.researchgate.net/profile/Riel_Miller2/publication/243995158_Being_without_existing_The_futures_community_at_a_turning_point_A_comment_on_Jay_Ogilvy%27s_Facing_the_fold/links/53f70d4d0cf22be01c452fae/Being-without-existing-The-futures-community-at-a-turning-point-A-comment-on-Jay-Ogilvys-Facing-the-fold.pdf

 

 

THE COMPLEXITY OF ANTICIPATION

Roberto Poli

Balkan Journal of Philosophy. 2009;1(1):19-29.

 

 

The Discipline of Anticipation: Exploring Key Issues

Riel Miller, Roberto Poli and Pierre Rossel

 

Clock of the Long Now: Time and Responsibility

Clock of the Long Now: Time and Responsibility

 

Stewart Brand is one of my Hero.  I admire his work and have deep respect for him.

Check out his books:

  • The Media Lab
  • Whole Earth Discipline
  • How Buildings Learn
  • Clock of the Long Now

Stewart Brand and his associates are building a 10000 yr clock in west Texas.  Project is funded by Jeff Bezos.  Danny Hillis is one of the designer of the clock.  Prototypes of clock are in display in Museums in UK and here in USA.

Stewart Brand work is about promoting long term thinking—Very Long Term Thinking.  What we call long term in our day to day conversation is just Now a days in context of Long Term Thinking being promoted by Stewart Brand.

Long Now thinking would be considered equal to thinking associated with climate cycles time scales such as Milankovitch Cycles.

You can check out current status of the clock and other projects of the Long Now Foundation at its website.

  • How should Humans live and behave in context of Long Term Thinking?
  • How should the information, knowledge, culture, artifacts, languages, species, ecology be preserved?
  • What kind of world are we creating for future generations?
  • What should be preserved?
  • How should it be preserved?
  • How would people after 10000 years extract information contained in preserved objects?

These are big and deep questions?  We need philosophers like Stewart Brand to guide us.

I am ready to learn from him and other visionaries like him.

 

Time Horizon – Short to Very Long Term

  • Now – 3 Days
  • Now a days – 30 years
  • Long Now – 20000 years

 

Types of Cycles – slow moving to fast moving

  • Nature
  • Culture
  • Governance
  • Infrastructure
  • Commerce
  • Fashion

 

Image of Long Now Time

layersoftime-simplnew

 

LongNowDiag

 

Key Sources of Researches:

 

Whole Earth comes into focus

To understand how our planet uses energy, we must integrate genetic data from microbial studies with satellite views of our planet.

 

Stewart Brand

 

https://pdfs.semanticscholar.org/e2df/859231b770b7370c630252e3d04867fa6b9a.pdf

 

 

An Architecture of the Whole

University of California, Davis

 

http://arts.berkeley.edu/wp-content/uploads/2016/01/arc-of-life-Sadler-.pdf

 

 

ECOLOGICAL FUTURES: BUILDING AN ECOLOGY OF THE LONG NOW

STEPHEN R. CARPENTER

 

http://esa.org/history/Awards/papers/Carpenter_SR_MA.pdf

 

 

“THE CLOCK OF THE LONG NOW”
A Talk with Stewart Brand

https://www.edge.org/documents/archive/edge46.html

 

 

The Clock in the Mountain

2011

http://kk.org/thetechnium/the-clock-in-th/

 

 

How to Make a Clock Run for 10,000 Years

2011

https://www.wired.com/2011/06/10000-year-clock/all/1

 

 

TIME IN THE 10,000-YEAR CLOCK

Danny Hillis, Rob Seaman, Steve Allen, and Jon Giorgini

 

https://arxiv.org/ftp/arxiv/papers/1112/1112.3004.pdf

 

 

Stewart Brand: The Long Now

 

 

 

The Long Now Foundation

http://longnow.org/clock/

 

 

There’s a Massive 10,000 Year Clock Being Built in a West Texas Mountain

BY ELIZABETH ABRAHAMSEN

2016

http://www.wideopencountry.com/there-is-a-10000-year-clock-under-construction-in-west-texas/