No open access version available yet, AFAIK
Source: The sociocybernetics of observation and reflexivity – Bernard Scott, 2019
A view or perspective on the world
No open access version available yet, AFAIK
Source: The sociocybernetics of observation and reflexivity – Bernard Scott, 2019
Preface available for download
Source: (99+) (PDF) Recursivity and Contingency | Yuk Hui – Academia.edu
Not much detail yet!
Source: Cybernetics in Late Soviet Culture: • Kultur • Osteuropa-Institut

17.06.2019
Workshop: Cybernetics in Late Soviet Culture
News vom 10.04.2019
The discourse on cybernetics is one of the most inspiring and thought-provoking intellectual currents in post-war science. As a truly interdisciplinary approach linking physics, psychology, computer science, sociology, philosophy and many disciplines more, its influence is topical in current epistemological understandings of “systemic” thinking. Although the history of cybernetics has been studied for the Western and Latin American context, cybernetics in the East European context has been brought to our fore only to some extent. Our workshop on June 17th aims to address cybernetics from an interdisciplinary point of view, linking historical and philosophical approaches with insights from literary and cultural studies. It is centered on the period from the early 1950s to the late 1970s and wants to draw attention to the peculiarities of Soviet and Socialist cybernetic thinking.
Programme and speakers t.b.a.
They are just one of the fears with developing technology, but such bots have been here for much longer than you think, writes Mike Ryder
Humans will always make the final decision on whether armed robots can shoot, according to a statement by the US Department of Defence. Their clarification comes amid fears about a new advanced targeting system, known as Atlas, that will use artificial intelligencein combat vehicles to target and execute threats. While the public may feel uneasy about so-called “killer robots”, the concept is nothing new – machine-gun wielding “Swords” robots were deployed in Iraq as early as 2007.
Our relationship with military robots goes back even further than that. This is because when people say “robot”, they can mean any technology with some form of autonomous element that allows it to perform a task without the need for direct human intervention.
These technologies have existed for a very long time. During the Second World War, the proximity fuse was developed to explode artillery shells at a predetermined distance from their target. This made the shells far more effective than they would otherwise have been by augmenting human decision making and, in some cases, taking the human out of the loop completely.
So the question is not so much whether we should use autonomous weapon systems in battle – we already use them, and they take many forms. Rather, we should focus on how we use them, why we use them, and what form – if any – human intervention should take.
The birth of cybernetics
My research explores the philosophy of human-machine relations, with a particular focus on military ethics, and the way we distinguish between humans and machines. During the Second World War, mathematician Norbert Wiener laid the groundwork of cybernetics – the study of the interface between humans, animals and machines – in his work on the control of anti-aircraft fire. By studying the deviations between an aircraft’s predicted motion, and its actual motion, Wiener and his colleague Julian Bigelow came up with the concept of the “feedback loop”, where deviations could be fed back into the system in order to correct further predictions.
Wiener’s theory therefore went far beyond mere augmentation, for cybernetic technology could be used to pre-empt human decisions – removing the fallible human from the loop, in order to make better, quicker decisions and make weapons systems more effective.
In the years since the Second World War, the computer has emerged to sit alongside cybernetic theory to form a central pillar of military thinking, from the laser-guided “smart bombs” of the Vietnam era to cruise missiles and Reaper drones.
It’s no longer enough to merely augment the human warrior as it was in the early days. The next phase is to remove the human completely – “maximising” military outcomes while minimising the political cost associated with the loss of allied lives. This has led to the widespread use of military drones by the US and its allies. While these missions are highly controversial, in political terms they have proved to be preferable by far to the public outcry caused by military deaths.
Continues in source: Killer robots are not science fiction – they have been part of military defence for a while | The Independent
Source: Pace Layering: How Complex Systems Learn and Keep Learning
“Civilizations with long nows look after things better,” says Brian Eno. “In those places you feel a very strong but flexible structure which is built to absorb shocks and in fact incorporate them.”
You can imagine how such a process could evolve—all civilizations suffer shocks; only the ones that absorb the shocks survive. That still doesn’t explain the mechanism.In recent years a few scientists (such as R. V. O’Neill and C. S. Holling) have been probing the same issue in ecological systems: how do they manage change, how do they absorb and incorporate shocks? The answer appears to lie in the relationship between components in a system that have different change-rates and different scales of size. Instead of breaking under stress like something brittle, these systems yield as if they were soft. Some parts respond quickly to the shock, allowing slower parts to ignore the shock and maintain their steady duties of system continuity.
Consider the differently paced components to be layers. Each layer is functionally different from the others and operates somewhat independently, but each layer influences and responds to the layers closest to it in a way that makes the whole system resilient.
From the fastest layers to the slowest layers in the system, the relationship can be described as follows:
Fast learns, slow remembers. Fast proposes, slow disposes. Fast is discontinuous, slow is continuous. Fast and small instructs slow and big by accrued innovation and by occasional revolution. Slow and big controls small and fast by constraint and constancy. Fast gets all our attention, slow has all the power.
All durable dynamic systems have this sort of structure. It is what makes them adaptable and robust.
Take a coniferous forest. The hierarchy in scale of pine needle, tree crown, patch, stand, whole forest, and biome is also a time hierarchy. The needle changes within a year, the crown over several years, the patch over many decades, the stand over a couple of centuries, the forest over a thousand years, and the biome over ten thousand years. The range of what the needle may do is constrained by the crown, which is constrained by the patch and stand, which are controlled by the forest, which is controlled by the biome. Nevertheless, innovation percolates throughout the system via evolutionary competition among lineages of individual trees dealing with the stresses of crowding, parasites, predation, and weather. Occasionally, large shocks such as fire or disease or human predation can suddenly upset the whole system, sometimes all the way down to the biome level.
The mathematician and physicist Freeman Dyson makes a similar observation about human society:
The destiny of our species is shaped by the imperatives of survival on six distinct time scales. To survive means to compete successfully on all six time scales. But the unit of survival is different at each of the six time scales. On a time scale of years, the unit is the individual. On a time scale of decades, the unit is the family. On a time scale of centuries, the unit is the tribe or nation. On a time scale of millennia, the unit is the culture. On a time scale of tens of millennia, the unit is the species. On a time scale of eons, the unit is the whole web of life on our planet. Every human being is the product of adaptation to the demands of all six time scales. That is why conflicting loyalties are deep in our nature. In order to survive, we have needed to be loyal to ourselves, to our families, to our tribes, to our cultures, to our species, to our planet. If our psychological impulses are complicated, it is because they were shaped by complicated and conflicting demands.
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In terms of quantity, there are a great many pine needles and a great many humans, many forests and nations, only a few biomes and cultures, and but one planet. The hierarchy also underlies much of causation and explanation. On any subject, ask a four-year-old’s sequence of annoying “Why?”s five times and you get to deep structure. “Why are you married, Mommy?” “That’s how you make a family.” “Why make a family?” “It’s the only way people have found to civilize children.” “Why civilize children?” “If we didn’t, the world would be nothing but nasty gangs.” “Why?” “Because gangs can’t make farms and cities and universities.” “Why not?” “Because they don’t care about anything larger than themselves.”
I propose six significant levels of pace and size in the working structure of a robust and adaptable civilization. From fast to slow the levels are:
In a durable society, each level is allowed to operate at its own pace, safely sustained by the slower levels below and kept invigorated by the livelier levels above. “Every form of civilization is a wise equilibrium between firm substructure and soaring liberty,” wrote the historian Eugen Rosenstock-Huessy.
Each layer must respect the different pace of the others. If commerce, for example, is allowed by governance and culture to push nature at a commercial pace, then all-supporting natural forests, fisheries, and aquifers will be lost. If governance is changed suddenly instead of gradually, you get the catastrophic French and Russian revolutions. In the Soviet Union, governance tried to ignore the constraints of culture and nature while forcing a five-year-plan infrastructure pace on commerce and art. Thus cutting itself off from both support and innovation, it was doomed.We can examine the array layer by layer, working down from the fast and attention-getting to the slow and powerful. Note that as people get older, their interests tend to migrate to the slower parts of the continuum. Culture is invisible to adolescents but a matter of great concern to elders. Adolescents are obsessed with fashion while elders are bored by it.
The job of fashion and art is to be froth—quick, irrelevant, engaging, self-preoccupied, and cruel. Try this! No, no, try this! It is culture cut free to experiment as creatively and irresponsibly as the society can bear. From all that variety comes driving energy for commerce (the annual model change in automobiles) and the occasional good idea or practice that sifts down to improve deeper levels, such as governance becoming responsive to opinion polls, or culture gradually accepting “multiculturalism” as structure instead of just entertainment.
If commerce is completely unfettered and unsupported by watchful governance and culture, it easily becomes crime, as in some nations after Communism fell. Likewise, commerce may instruct but must not control the levels below it, because it’s too short-sighted. One of the stresses of our time is the way commerce is being accelerated by global markets and the digital and network revolutions. The proper role of commerce is to both exploit and absorb those shocks, passing some of the velocity and wealth on to the development of new infrastructure, but respecting the deeper rhythms of governance and culture.
Infrastructure, essential as it is, can’t be justified in strictly commercial terms. The payback period for things such as transportation and communication systems is too long for standard investment, so you get government-guaranteed instruments like bonds or government-guaranteed monopolies. Governance and culture have to be willing to take on the huge costs and prolonged disruption of constructing sewer systems, roads, and communication systems, all the while bearing in mind the health of even slower “natural” infrastructure—water, climate, etc.
Education is intellectual infrastructure. So is science. They have very high yield, but delayed payback. Hasty societies that can’t span those delays will lose out over time to societies that can. On the other hand, cultures too hidebound to allow education to advance at infrastructural pace also lose out.
In the realm of governance, the most interesting trend in current times—besides the worldwide proliferation of democracy and the rule of law——is the rise of what is coming to be called the “social sector.” The public sector is government, the private sector is business, and the social sector is the nongovernmental, nonprofit do-good organizations. Supported by philanthropy and the toil of volunteers, they range from church charities, local land trusts, and disease support groups to global players like the International Red Cross and World Wildlife Fund. What they have in common is that they serve the larger, slower good.
The social sector acts on culture-level concerns in the domain of governance. One example is the sudden mid-20th-century dominance of “historic preservation” of buildings, pushed by organizations like the National Trust for Historic Preservation in America and English Heritage and the National Trust in Britain. Through them, culture declared that it was okay to change clothing at fashion pace, but not buildings; okay to change tenants at commercial pace, but not buildings; okay to change transportation at infrastructure pace, but not neighborhoods. “If some parts of our society are going to speed up,” the organizations seemed to say, “then other parts are going to have to slow way down, just to keep balance.” Even New York City, once the most demolition-driven metropolis in America, now is preserving its downtown.
Culture’s vast slow-motion dance keeps century and millennium time. Slower than political and economic history, it moves at the pace of language and religion. Culture is the work of whole peoples. In Asia you surrender to culture when you leave the city and hike back into the mountains, traveling back in time into remote village culture, where change is century-paced. In Europe you can see it in terminology, where the names of months (governance) have varied radically since 1500, but the names of signs of the Zodiac (culture) are unchanged in millennia. Europe’s most intractable wars have been religious wars.
As for nature, its vast power, inexorable and implacable, just keeps surprising us. The world’s first empire, the Akkadian in the Tigris-Euphrates valley, lasted only a hundred years, from 2300 BCE to 2200 BCE. It was wiped out by a drought that went on for three hundred years. Europe’s first empire, the Minoan civilization, fell to earthquakes and a volcanic eruption in the 15th century BCE. When we disturb nature at its own scale, such as with our “extinction engine” and greenhouse gases, we risk triggering apocalyptic forces. Like it or not, we have to comprehend and engage the longest now of nature.
The division of powers among the layers of civilization lets us relax about a few of our worries. We don’t have to deplore technology and business changing rapidly while government controls, cultural mores, and “wisdom” change slowly. That’s their job. Also, we don’t have to fear destabilizing positive-feedback loops (such as the Singularity) crashing the whole system. Such disruption can usually be isolated and absorbed. The total effect of the pace layers is that they provide a many-leveled corrective, stabilizing feedback throughout the system. It is precisely in the apparent contradictions between the pace layers that civilization finds its surest health.
The idea of pace layering has a history. The text above is a slightly edited version of a chapter in my 1999 book The Clock of the Long Now: Time and Responsibility. I first created the healthy-civilization diagram with Brian Eno at his studio in London in 1996. Earlier still, in the early 1970s, the English architect Frank Duffy wrote, “A building properly conceived is several layers of longevity of built components.” He identified four layers in commercial buildings—Shell (lasts maybe 50 years), Services (swapped out every 15 years or so), Scenery (interior walls, etc. move every 5 to 7 years), and Set (furniture, moving sometimes monthly.) For my 1994 book How Buildings Learn: What Happens After They’re Built I expanded Duffy’s four layers to six: Site, Structure, Skin, Services, Space Plan, and Stuff. The chapter on how the components play out in a healthy building I titled “Shearing Layers.” Some reviewers of the book on Amazon claim that How Buildings Learn is really about software and systems design.
“Networks are an essential ingredient in any complex adaptive system,” Eric Beinhocker writes in The Origin of Wealth. “Without interactions between agents, there can be no complexity.”
Think of a printed page in a book for a moment. It may contain complex ideas, but it is relatively simple. It is hard-linked to the page that came before and the one after. It may contain references which leads you to an appendix. However, in many ways, it is what you may call “finished” or “published”.
Webpages have a whole other level of potential. They may in fact be just like that print page if an organization has merely digitized print content and uploaded it on the Web. However, it is usually surrounded by an architecture of links. Sometimes, it may contain live data that gets updated as and when change occurs. Sometimes, it will change based on an action by the one accessing it. That is the true Web. And when it is at its most powerful, it is also at its most complex.
However, this is generally a hidden complexity. Think of Google. It couldn’t be simpler to use: a search box and a click. Its interface has become even more minimal over the years. Up until sometime in 2015, it had a link beside the search box that read, “Advanced Search.” It no longer has that link, even though, year after year, the search algorithm has been refined to become more and more complex.
Google removed the link “Advanced Search” simply because most people didn’t want to do an “advanced” search. “Why, little old me, I’d never be able to do any advanced search. Sounds very complex. Do you need a degree for that?”
Google realized it needed to perform the advanced and complex work for the customer. Thus, instead of the customer going to the advanced section and selecting an option that indicated they wanted to conduct geographical searches, Google sought to identify words in their search behavior that would indicate whether they were searching for a place rather than a thing or person. If Google noticed such “geographic” words, it would include a map in its search results.
We all want the fruits of complexity. Only a few want to undertake the labors of complexity to make things simpler for others. If you consider the history of retail – from barter to Amazon – we see an inexorable shift of complexity away from the buyer and towards the seller. The seller is constantly and relentlessly making it easier to purchase because sellers have done the math. They understand the return on investment when investing in simplicity.
Most other organizations do not invest in simplicity. They constantly calculate the costs of complexity they will incur, ignoring the returns on simplicity. They seek the cheapest ways to get stuff up on the Web (which is why we see so much digitized print content in the form of bulky PDFs on websites).
The Web is not print. It’s a much more complex, networked environment. Those who are investing in complexity, while also investing in simplifying interactions with such complex systems, are reaping the bountiful rewards.
Paid courses for teachers (I think)
Source: Online Courses – CC Modeling Systems

The first online course in the sequence of System Dynamics (SD) modeling courses is intended for any instructor who does not have experience with SD modeling. The participant will learn to build the models presented using lessons that they could adapt for their own students. The model-building lessons have been used in math and/or science classes, some with students as young as 15 years. The course is asynchronous.
Prerequisites: 1. Comfort with basic secondary school algebra concepts; 2. Comfort with the content of the course being taught by the participant (within which model-building activities will be added); 3. An interest in expanding the hands-on experiences of the participants’ students; 4. An interest in learning the value that System Dynamics modeling can bring to the learning environment.
The sequence of session topics are listed below:
Each session is divided into sections that involve exploring the new concepts, practicing the new concepts, an assessment, reading and discussion questions, and numerous web resources. (Maximum 15 participants.)

The second online course in the sequence of System Dynamics (SD) modeling courses is intended for instructors who want to go the next step, building models dealing with more advanced system dynamics concepts. The participant will learn to build the models presented using lessons that they could adapt for their own students. The model-building lessons have been used in math and/or science classes, some with students as young as 15 years. The course is asynchronous.
Prerequisites: 1st Course in System Dynamics Modeling: Basic Models. Or, participants need: 1. experience building small System Dynamics (SD) models (especially containing exponential structure); 2. the ability to include appropriate, consistent units in an SD model; 3. the ability to recognize and explain reinforcing and balancing feedback loops in an SD model.
The sequence of session topics are listed below:
Each session is divided into sections that involve exploring the new concepts, practicing the new concepts, an assessment, reading and discussion questions, and numerous web resources. (Maximum 15 participants.)

The third online course in the sequence of System Dynamics (SD) modeling courses is intended for instructors who want to learn to build original models whose inspiration arises from news articles or from course content for which there are currently no available SD models. The participant will learn even more advanced SD techniques and practice building some pre-designed models as well as original models. There is a modeling project required for this course that will take the participants through the entire SD modeling method. The model-building lessons have been used in math, science, social science, and/or economics classes, some with students as young as 15 years of age. Most of the course is asynchronous. There are parts of two lessons for which a time will be synchronized for group model building.
Prerequisites: 2nd Course in System Dynamics Modeling: More Advanced Models. Or, participants need: 1. experience building System Dynamics (SD) models containing at least 2 – 3 stocks; 2. the ability to design and apply a dimensionless multiplier in an SD model; 3. the ability to define consistent units and identify and explain feedback in an SD model; 4. to understand the meaning of transfer of loop dominance.
The sequence of session topics are listed below:
Each session is divided into sections that involve exploring the new concepts, practicing the new concepts, an assessment, reading and discussion questions, and numerous web resources. (Maximum 15 participants.)
Instructors for Course 1:
Anne LaVigne: In collaboration with the Creative Learning Exchange, create materials and experiences that engage people in basic modeling concepts and connect educators to real-world curricular systems being studied in pre-college education.
Diana Fisher: Winner of the Lifetime Achievement Award (2011 – System Dynamics Society); Presidential Award (1995); Intel Innovation in Teaching Award (1996). Teacher of system dynamics modeling at the pre-college and university level for over 20 years.
Instructor for Course 2 and Course 3:
Diana Fisher
Roth S. (2019), The open theory and its enemy: Implicit moralisation as epistemological obstacle for general systems theory, Systems Research and Behavioral Science, Vol. 36 No. 3, 1-8 [SSCI .860, Scopus, CABS**].
Article available for download here.
Abstract: Ludwig von Bertalanffy decisively shaped open systems theory as challenge and alternative to the then‐dominant theories of closed systems. This strategic positioning and its success have abetted frequent and frequently implicit moralisations of openness and closeness. In this article, we draw on the concept of autopoietically closed systems to show that the prevailing affirmative bias to openness constitutes an epistemological obstacle to the advancement of general systems theory. We demonstrate how this obstacle can be removed by tetralemmatic decision programmes that facilitate the management of dilemmatic co‐occurrences of and trade‐offs between openness and closeness.
Keywords: autopoietic systems, Bertalanffy, epistemological obstacles, general systems theory, Luhmann, open systems, tetralemma
Source: Ackoff Center Weblog: The Causal Texture of Organizational Environments
F.E. Emery and E.L. Trist, ‘The causal texture of organizational environments’, Human Relations vol.18 (1965), pp. 21-32. Reprinted with Permission
A main problem in the study of organization change is that the environmental contexts in which organizations exists are themselves changing, at an increasing rate, and towards increasing complexity. This point, in itself, scarcely needs labouring. Nevertheless, the characteristics of organisational environments demand consideration for their own sake, if there is to be an advancement of understanding in the behavioural sciences of a great deal that is taking place under the impact of technological change, especially at the present time. This paper is offered as a brief attempt to open up some of the problems, and stems from a belief that progress will be quicker if a certain extension can be made to current thinking about systems. In a general way it may be said that to think in terms of systems seems the most appropriate conceptual response so far available when the phenomena under study – at any level and in any domain – display the character of being organised, and when understanding the nature of the interdependencies constitutes the research task. In the behavioural sciences, the first steps in building a systems theory were taken in connection with the analysis of internal processes in organisms, or organisation, when the parts had to be related to the whole. Examples include the organismic biology of Jennings, Cannon, and Henderson; early Gestalt theory and its later derivatives such as balance theory; and the classical theories of social structure. Many of these problems at the social level. It will show how a greater degree of system-connectedness, of crucial relevance to the organization, many develop in the environment, which is yet not directly a function either of the organization’s own characteristics or of its immediate relations. Both of these, of course, once again become crucial when the response or the organization to what has been happening is considered.
This is an ‘eccentric’ site in its design and colour scheme, but the content including key diagrams is useful. Above the below content on the page linked is a CV and timeline of Ansoff.
Source: H. Igor Ansoff – Strategic Posture
“Igor Ansoff ‘invented’ strategic planning and strategic management.” Philip Kotler
“Igor Ansoff is the father of strategic management.” Henry Mintzberg
“Truly the godfather of Corporate strategy.” Gary Hamel
“Igor Ansoff was the father of modern strategic thinking.” Tim Hindle
“In 1965 came the Bible of strategic planning, H. Igor Ansoff’s monumental Corporate Strategy.” Richard Koch
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Guy Parrott
The Ansoff’s matrix and its relevance in today’s marketing University of Bedfordshire |
Malcolm McDonald
Ansoff Matrix The Oxford College of Marketing |
Contribution1. Founder of the concept of Strategic Management:
. was the first to coin the term Strategic Planning (1965) . and, later on the term Strategic Management (1972)2. First to introduce the Umbrella Concept suggesting that different solutions are needed under different levels of turbulence of the Environment. These solutions include business and corporate level strategies.3. Empirically validated theories, proven in thousands of situations around the world 4. Developed the Strategic Success Diagnosis model to determine and assess an Organization’s external Environment as to: 5. The Strategic Success Diagnosis applies to all Environment Serving Organizations, for profit, not-for profit and governmental agencies 6. Concentrated on the strategies and capabilities needed at the high levels of turbulence of the Environment by introducing the Real-Time Strategic Management concept 7. Developed many practical process tools and technologies applied in practice |
ValidationH. Igor Ansoff came to USIU in 1983 and founded the School of Strategic Management. He is the only one in the field who has validated his theory supported with consistently high results. There are over 45 Doctorates awarded in the Strategic Management discipline verifying Ansoff’s approach. The findings were empirically validated. All results are available for review at a special edition Compendium of Strategic Management Research. Graduates of the Strategic Management program, from both the Master’s and the Doctoral programs, are holding high positions in industry and academia around the world. |
Judge the results by the criterion of relevance to reality, and not by the more common criterion of proper attribution to prior work.
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It is a model of the business environment consisting of five turbulence levels, ranging from placid and predictable to highly changeable and unpredictable. For each level of turbulence, Ansoff hypothesized and proven that a different behavior is needed in each level which optimizes an organization’s profitability (1979). A simplified description of the levels of turbulence is shown.
In order for an organization to balance both the strategic and operational components, it has to look at both the external and internal environments and align its position to achieve good results. This led to the realization that analysis and interpretation of the organization’s external environment is pivotal to its strategic success. Ansoff constructed a five-point scale of ‘turbulence levels’. These are described by a combination of the changeability of events in the environment. The external environment serves as the key indicator for the organization’s strategic position and its inaccurate perception is “strategic myopia”. |
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Ansoff used the model of turbulence to construct a strategic success paradigm based on three variables: the turbulence levels of the organization’s environment; the aggressiveness of the organization’s strategic behavior in the environment; and the responsiveness of the organization’s management to changes to the environment.
The paradigm states that the financial performance of an organization is optimized when the aggressiveness and management responsiveness of the organization both match the turbulence of the organization’s environment (1979). The fact that an organization can be successful at one time and unsuccessful in another led Ansoff to realize that an organization’s strategy has to be aligned with the level of turbulence in which it operates; otherwise its financial performance drops. A matching triplet was designed to show the link between the environment, strategy and capability. Ansoff challenges the validity of prescriptions for organizations’ success established in the literature. His model does not deny the validity of these prescriptions; on the contrary it places them in a context in which each is valid under a particular set of circumstances dependent on the level of turbulence of the environment. For instance, specific strategic actions could be very appropriate in one level but not so when applied in another level. In order for organizations to attain maximum profitability, they have to interpret the level of environmental turbulence and align their strategy and capability accordingly. While some maintain that there is one prescription for success, Ansoff has empirically proven in a total of more than 2,100 cases around the world (1983 – 1999) that different environments call for different corporate responses. Ansoff developed a diagnostic tool for working managers to diagnose the readiness of their organizations to succeed in turbulent environments. It enables an organization to identify the existence of any gap between its future environment, its current strategy and its current capability. Managers can also use the paradigm to select the strategic approach proposed by the academics and consultants which best fit in the appropriate level of turbulence. There are quite a number of options applicable in each level of turbulence. However, the same strategic option does not guarantee optimal financial performance under all levels of turbulence. One can be appropriate for one but inappropriate for another. |
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Ansoff’s third contribution is in the applicable strategies to be used in high turbulence environments. The distinct characteristics of the real-time strategic management include the following: 1. Application of strategic diagnosis to assess the organization’s readiness to succeed in the high turbulent environment |
Source: Strategic Planning in Turbulent Environments: A Social Ecology Approach to Scenarios
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PDF Download (408kB) | Preview |
We contrast conventional strategic approaches derived from neoclassical economics with a socio-ecological approach to strategy. We propose that the socio-ecological approach, and specifically the causal textures theory of organizational environments it spawned, helps strategic planners to better engage unpredictable uncertainty that characterizes turbulent environments. To support our argument, we render explicit three principles that have been implicit in causal textures theory. We articulate general strategic planning stances for organizations consistent with each of the three principles, and demonstrate how scenario planning can help to instantiate each principle. We conclude that causal textures theory helps strategic planners to better understand the purpose of scenario planning and helps to guide them on how to make use of scenario planning to effect better strategies in a turbulent environment.
| Item Type: | Article |
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| Keywords: | Strategy; entrepreneurship & global business; Environment uncertainty; High velocity environment; Inter-organizational relationships; Organizational ecology; stakeholder theory; strategy & innovation |
| Subject(s): | Strategy; Entrepreneurship & Global business |
| Date Deposited: | 14 Nov 2014 16:22 |
| Last Modified: | 08 Aug 2018 12:56 |
| Funders: | None |
| URI: | http://eureka.sbs.ox.ac.uk/id/eprint/5218 |
Have not had time to read but apparently has multiple cybernetics references…
Philosophical foundations for digital programming
Source: Personal History Of Computing – DEV Community 👩💻👨💻
Lorenzo (Mec-iS) Apr 14 ・8 min read“After the tool, responding only to his hand; after the machines, covering complex tasks and operations but subject to his will; here he is to delegate automata to take care of managing and thinking in place of himself, on the basis of apparently rational criteria.“ — H.J. Martin, 1988