Service Systems, Natural Systems: Sciences in Synthesis -- An Outline for a Presidential Address

David Ing, International Society for the Systems Sciences, President, 2011-2012
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This written outline is a complement to the presentation slides presented in the incoming presidential address at 55th Annual Meeting of the ISSS on July 22, 2011. Leading up to the 56th Annual Meeting scheduled for July 2012, members of the society are encouraged to look for towards opportunities where the systems approach can support the development of new perspectives on service science and natural science.

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jump to part [1 on the systems approach] [2 on service systems] [3 on natural systems] [4 on frames] [5 on learning and knowing]

0: Introduction -- Synthesis across the sciences of service systems and natural systems in a systems approach is a promising way to deal with complexity in our world

As we look forward into 2012, I encourage members of the ISSS to continue the development of sciences in synthesis. Synthesis means putting things together, rather than taking them apart. Synthesis leads to emergence: properties of a whole that are not in its parts. The research communities centered on service systems and on natural systems may benefit from a synthesis through a systems approach.

This presidential address has 6 parts.

  • 1. Challenges where the systems approach can make a contribution
  • 2. Research into service systems
  • 3. Research into natural systems
  • 4. Some frames brought with a systems approach
  • 5. Learning and knowing

The address concludes with a call for participation at the 56th annual meeting of the ISSS in San Jose, California, in July 2012.

1. The systems approach continues to have functions in appreciating interconnections and surfacing blind spots in our views of the world

Where is a systems approach valuable? We can think about this in 3 parts:

  • 1. Complexity in the 21st century
  • 2. The heritage of the systems movement
  • 3. A future for the systems movement

The value of the systems approach is associated with its functions to appreciate interconnections across a variety of systems, and to surface blind spots in our views of the world.

1.1 Issues in the 21st century world are often described as complex

The world, from the perspectives both from an average citizen and from world leaders, seems to be increasingly complex. In the 2011 World Economic Forum, these challenges were seen as risks.

The world has never been confronted with so many complex challenges at the same time. The role of the annual meeting in Davos is not just to address one of those challenges, but to provide a systemic, strategic overview about all that is important on the global agenda, and if possible, to come up with solutions, and how we should confront, as a multistakeholder community those challenges.

To name only some of the challenges, of course, it's the economic situation, it's the great volatility that we have not only in the capital markets, but food prices, commodity prices in general, and I could go on and on. Our risk report, which we will publish just in time for the annual meeting, will describe 34 of those challenges. [Schwab 2010]

In 2011, the World Economic Forum has identified risks in five domains:

  • Economic risks
  • Geopolitical risks
  • Environmental risks
  • Societal risks
  • Technological risks

These risk all depicted in as 37 risks in a landscape that depicts "perceived likelihood to occur in the next ten years" and "perceived impact in billion US $". We cannot, however, divide and conquer. The risks are all interconnected. This is a problematique in an era of rapid technological progress and social change.

This new dimension of technoological progress and social change is in its infancy. [....]

It is not only the velocity and nature of change, but also the increasing multiplicity of actors which characterizes the world of today and tomorrow. [....]

All of these accelerated trends -- velocity, multiplicity, interconnectivity -- are creating a completely new world in which the master of complexities will be the key challenge. Of course, the more complex the system is, the greater the risk of systemic breakdowns. [Schwab 2011]

Our modern world is estimated at a $64 trillion complex, dynamic and interconnected system of systems, with the large core systems being

  • (i) infrastructure ($22.54 trillion);
  • (ii) leisure / recreation / clothing ($7.80 trillion);
  • (iii) transportation ($6.95 trillion);
  • (iv) government and safety ($5.21 trillion) and
  • (v) food ($4.89 trillion).

An estimated $15 trillion is estimated as waste and loss through inefficiency in silos, of which $4 trillion could be eliminated. The largest percentage ineficiencies relative to the systems total economic value are in

  • (i) healthcare,
  • (ii) education,
  • (iii) government and safety,
  • (iv) building and transportation infrastructure, and
  • (v) electricity [IBM 2010].

Is this true that we have never faced this much complexity before? How might we, as scientists and citizens of the world, become part of the solutions rather than remaining as part of the problems?

1.2 The heritage of the system movement includes systems thinking, systems engineering, systems practice, and the systems sciences

These challenges of complexity were at the founding of the International Society for the Systems Sciences in 1954.

Early in the fall of 1954, four of the distinguished CASBS [Center for Advanced Studies in the Behavioral Sciences] fellows -- Bertalanffy, Boulding, Gerard, and Rapoport -- sat together at lunch discussing their mutual interest in theoretical frameworks relevant to the study of different kinds of systems, including physical, technological, biological, social, and symbolic systems. According to Boulding, someone suggested they form a society to foster interdisciplinary research on a general theory of complex systems, and thus the idea for the Society for General Systems Research (SGSR) was born. [Hammond 2003, p. 9]

The systems movement has a foundation in science that sweeps in many related perspectives, including systems thinking, systems engineering, systems practice and the systems sciences.

Systems thinking can be formally defined as ..

An epistemology which, when applied to human activity is based upon the four basic ideas: emergence, hierarchy, communcation, and control as characteristics of systems. When applied to natural or designed systems the crucial characteristic is the emergent properties of the whole. [Checkland 1981, p. 318]

Systems thinking, as a style, can be contrasted with the order of analysis and synthesis.

[In systems thinking] ... synthesis precedes analysis.

1. Identity a containing whole (system) of which the thing to be explained is a part.

2. Explain the behavior or property of the containing whole.

3. Then explain the behavior or properties of the thing to be explained in terms of its role(s) or function(s) within its containing whole. [Ackoff 1981, p. 16]

Systems engineering enables science to have an impact with progress through "organized creative technology":

... systems engineering ... attempts to shorten the time lags between scientific discoveries and their applications, and between the appearance of human needs and the production of new systems to satisfy those needs.

Systems engineering considers the content of the reservoir of new knowledge, then plans and participates in the action of projects and whole programs of projects leading to application. It considers the needs of its customers and determines how these can be best met in the light of all knowledge both old and new. Thus systems engineering operates in the space between research and business, and assumes the attitudes of both. [Hall 1965, pp. 3-4]

Systems practice sets a scope of human activity systems.

The idea of 'systems practice' implies a desire to find out how to use systems concepts in trying to solve problems. [....]

[A] possible approach to systems practiced aimed at real-world problem-solving .... can be tackled by identifying, designing, and implementing human activity systems. [Checkland 1981, p. 125]

Systems science has been associated with General Systems Theory.

The objectives of General Systems Theory then can be set out with varying degrees of ambition and confidence.

At a low level of ambition but with a high degree of confidence it aims to point out similarities in the theoretical constructions of different disciplines, where these exist, and to develop theoretical models having applicability to at least two different fields of study.

At a higher level of ambition, but with perhaps a lower degree of confidence it hopes to develop something like a "spectrum" of theories - a system of systems which may perform the function of a "gestalt" in theoretical construction. Such "gestalts" in special fields have been of great value in directing research towards the gaps which they reveal. [Boulding 1956, p. 198]

Thus, the research in the systems sciences has a unique function to assist disciplinary sciences with gaps that they themselves may or may not appreciate.

1.3 A future for the systems movement can be in continuing to learn about "unknown unknowns"

The systems movement hs the benefit of a long tradition of learning. Learning may be associated with process, in a five level categorization by Bateson.

Zero learning is characterized by specificity of response, which -- right or wrong -- is not subject to correction. [....]

Learning I is change in specificity of response by correction of errors of choice within a set of alternatives. [....]

Learning II is change in the process of Learning I, e.g., a corrective change in the set of alternatives from which choice is made, or it is a change in how the sequence of experience is punctuated. [....]

Learning III is change in the process of Learning II, e.g., a corrective change in the system of sets of alternatives from which choice is made. (We shall see later that to demand this level of performance of some men and some mammals is sometimes pathogenic.) [....]

Learning IV would be change in Learning III, but probably does not occur in any adult living organism on this earth. Evolutionary process has, however, created organisms whose ontogeny brings them to Level III. The combination of phylogenesis with ontogenesis, in fact, achieves Level IV. [....] [Bateson 1972]

In the Curriculum on Medical Ignorance at the University of Arizona College of Medicine, the portrayal of confidence in findings by doctors is appreciated, but physicians should also be mindful of the limits of science. [Witte, Kerwin, Witte 1998]

Ignorance can be approached in four areas:

  • known unknowns;
  • passive ignorance, as ignoring (which includes errors and unknown knowns)
  • unknown knowns; and
  • active ignorance, as the ignored (which includes taboos and denials). [Ing, Takala and Simmonds, 2003]

These are each handled in different ways:

  • Known Unknowns are gaps where competence development is clearly motivated
    • A known unknown presents itself as a deficiency in a current organizational competence
    • Known unknowns can be cleared with continued evolution of current competences
  • Passive ignorances includes errors and unknown knowns localized in competences
    • Exploiting errors and unknown knowns leverages known competences elsewhere
    • Ignoring can be overcome through self-reflection, criticism, review and cross-functional competence sharing
  • Unknown unknowns test the ability of competences to handle surprises
    • Unknown unknowns test the robustness and flexibility of organizational competences
    • Unknown unknowns can’t be fought, but must be embraced in competence development
  • Active ignorances are “the ignored” taboos and denials of alternative competences
    • The ignored of taboos and denials reflect an arrogance on the “best” competences
    • Overcoming the ignored requires listening to alternative voices with credibility [Ing, Takala and Simmonds, 2003]

Ignorance may be disclosed through self-discovery, or by customers and competitors

In addition to the heritage community, two other communities of researchers and practitioners are on convergent paths: (i) the group associated with the emerging field of service science, management, engineering and design, and (ii) the group associated with resilience science and sustainability.

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2. Service scientists are researching global post-industrial shifts, coproduction of outcomes and the newly-observable unobserved

Where are scientists researching service systems working? This can be outlined in 3 parts:

  • 1. Forms of service systems and challenges
  • 2. Coproduction of outcomes, interactive value
  • 3. The unobservable becoming observable

Some service scientists already have foundations in the systems sciences. Others will require some encouragement and coaching to appreciate a systems approach.

2.1 Human civilization is served by systems in technical, organizational and socio-political forms

In the 21st century, the range of service systems that will benefit from better preparation through education and lifelong learning experiences is slightly different from the industrial age orientation the 20th century. From simplest to most complicated, the systems

  • (i) move, store, harvest and process;
  • (ii) enable healthy, wealthy and wise people, and
  • (iii) govern. [Spohrer and Maglio 2010, p. 184]
Spohrer and Maglio 2010: Types of service systems
Systems that move, store, harvest, process Transportation K
Water and waste management 1
Food and global supply chain 2
Energy and energy grid 3
Information and communications technology (ICT) infrastructure 4
Systems that enable healthy, wealthy and wise people Building and construction 5
Banking and finance 6
Retail and hospitality 7
Healthcare 8
Education (including universities) 9
Systems that govern Government (cities) 10
Government (regions / states) 11
Government (nations) 12

The distinction between definition of a service system, as compared to a system, lies in the value created and delivered through parties.

A service system can be defined as a dynamic configuration of resources (people, technology, organisations and shared information) that creates and delivers value between the provider and the customer through service.

In many cases, a service system is a complex system in that configurations of resources interact in a non-linear way. Primary interactions take place at the interface between the provider and the customer. However, with the advent of ICT,

customer-to-customer and supplier-to-supplier interactions have also become prevalent. These complex interactions create a system whose behaviour is difficult to explain and predict. [IfM and IBM 2008, p. 6]

From an engineering perspective, the shift to service systems from goods-oriented systems can associated with three 21st century shifts: (i) the emergence of electronic services; (ii) the relationship of services to manufacturing, and (iii) the movement towards mass customization of both goods and services [Tien 2008].

Electronic services are totally dependent on information technology

Tien 2008, Table II: Comparison of Traditional and Electronic Services
. Service Enterprises
Issue Traditional Electronic
Co-Production Medium Physical Electronic
Labor Requirement High Low
Wage Level Low High
Self-Service Requirement Low High
Transaction Speed Requirement Low High
Computation Requirement Medium High
Data Sources Multiple Homogenous Multiple Non-Homogenous
Driver Data-Driven Information-Driven
Data Availability/Accuracy Poor Rich
Information Availability/Accuracy Poor Poor
Size Economies of Scale Economies of Expertise
Service Flexibility Standard Adaptive
Focus Mass Production Mass Customization
Decision Time Frame Predetermined Real-time

"The goods sector requires material as input, is physical in nature, involves the customer at the design stage, and employs mostly quantitative measures to assess its performance. On the other hand, the services sector requires information as input, is virtual in nature, involves the customer at the production/delivery stage, and employs mostly qualitative measures to assess its performance." [Tien 2008, p. 148]

Tien 2008, Table III: Services Versus Manufactured Goods
Focus Services Manufactured Goods
Production Co_Produced Pre-Produced
Variability Heterogeneous Identical
Physicality Intangible Tangible
Product Perishable "Inventoryable"
Objective Personalizable Reliable
Satisfaction Expectation-Related Utility-Related
Life Cycle Reusable Recyclable

Towards mass customization, a value chain can be defined and then partitioned into supply and demand chains.

Tien 2008, Table IV: Research Taxonomy for Demand and Supply Chains
Supply Demand
Fixed Flexible
Fixed Unable to Manage
  • Price Established (At Point Where Fixed Demand Matches Fixed Supply)
Demand Chain Management (DCM)
  • Product Revenue Management
  • Dynamic Pricing
  • Target Marketing
  • Expectation Management
  • Auctions
Flexible Supply Chain Management (SCM)
  • Inventory Control
  • Production Scheduling
  • Distribution Planning
  • Capacity Revenue Management
  • Reverse Auctions
Real-Time Customized Management (RTCM)
  • Customized Bundling
  • Customized Revenue Management
  • Customized Pricing
  • Customized Modularization
  • Customized Co-Production System

The service systems perspective is now entering a stage of early maturity, with the publication of works such as The Science of Service Systems [Demirkan, Spohrer and Krishna 2011]

2.2. Coproduction of outcomes, interactive value

In systems theory, coproduction is one type of producer-product relation, in contrast to a cause-effect relation. The most rigourous formalism related to coproduction takes 5 pages to build up the following definition in Ackoff & Emery (1972)

2.31. Coproducers: two or more objects, properties and/or environments that are producers of the same product.

Since no producer is ever sufficient for its product, every producer has at least one coproducer. The set of all coproducers of a product y is the cause of y, since the set is sufficient as well as necessary for y. [Ackoff and Emery 1972, p. 23]

To be rigourous, there’s a fine distinction making the linkage between action, product and outcome, in Ackoff & Emery (1972):

2.40. Outcome: the product of an individual’s or system’s action.

In other words, the outcome of an individual’s or system’s action is a change in that individual or system, or its environment, which is produced by that action. [Ackoff and Emery 1972, p. 26]

The distinctions between cause-effect and producer-product are expressed less mathematically in Ackoff (1981).

As Singer (1959) and Ackoff and Emery (1972) have shown, the view of the universe revealed by viewing it in terms of producer-product is quite different from that yielded by viewing it in terms of cause-effect. Because a producer is only necessary and not sufficient for its product, it cannot provide a complete explanation of it. There are always other necessary conditions, coproducers of its product. For example, moisture is a coproducer of an oak along with an acorn. These other necessary conditions taken collectively constitute the acorn’s environment. Therefore the use of the producer-product relationship requires the environment to explain everything whereas use of cause-effect requires the environment to explain nothing. Science based on the producer-product relationship is environment-full, not environment-free.

A law based on the producer-product relationship must specify the environment(s) under which it applies. No such law can apply in every environment, because if it did, no environmental conditions would be necessary. Thus there are no universal laws in this view of the universe. [Ackoff 1981, p. 21]

While mechanical systems are usually modeled as cause-effect, a service system is a social system. In the creation of value, the supplier and customer take action together as coproducers of an outcome. Other third parties (e.g. subcontractor) may also be coproducers. A cause-effect relation may exclude inputs and outputs insignificant in one environment, but significant in another. As an example in a service system, autopilot is now standard on all commercial aircraft, coproducing air travel with a complement of passengers. Arriving at a destination, however, is rarely done without a flight crew as a coproducer, because all of the inputs and outputs of each journey are neither exactly the same not foreseeable.

Interactive value is actualized not in coproduction of the supplier with customer, but in coproduction of the customer with his/her customer / counterparts.

There’s a danger in using the phrase value-creating system, in the intimation that the value might be in the system itself. In any discussion of creating value, we should be careful to ask: value for whom? From a system approach, the value isn’t in the parts, but in the interactions between the parts, as described by Ramírez and Wallin. 2000:

Facilitating customer value creation is, within the co-productive point of view, the raison d’être for a firm.

This perspective shifts the focus of strategic attention from actor or ‘activity’ to interaction. [Ramírez and Wallin 2000, p. 47]

It’s not just the customer, nor is it just the supplier. It’s the interacton between the two. Value is perceived by the customer, not in the customer-supplier coproduction, but yet another relationship beyond.

How is value produced from the point of view of the customer?

[... the] actualization of value takes place — that is, value is actually manifested — in the actual relationships between a customer and his or her customers or counterparts. In other words, for customers, value is not ‘added’ in the interaction between customer and supplier (when the customer buys [a white] shirt), but in the interaction between the customer and the customer’s customer or counterpart (when they buyer wears the shirt and her family and others see it on her). In co-productive terms, value is manifested thanks to the ‘enabling’ which the supplier brings to the customer’s own value creating activity. By ‘enabling’ we mean ‘supporting’ or ‘making possible’. [....]

It is thus not at the interface with the supplier that value is manifested for a customer, but at the interface between the customer and the customer’s customer or counterparts. [Ramírez and Wallin 2000, p. 43]

In this discussion of value, the word actual isn’t chosen lightly, but instead refers to the action that takes place.

Rather than being objective or subjective, interactive value is, in fact, ‘actual’. It is ‘actual’ in the sense that it requires action on the part of both the customer, and his or her customers, and supplier for the value to become (actually) possible. Once the actions take place, they become facts. Actual value is thus dependent on ‘action’ and interaction, which upon taking place ‘actually’, becomes ‘factual’.

With this understanding of customer valuation, the notion of ‘end customer’ — a customer at the end of the value chain that passively receives the value produced by the supplier — has lost its significance. Somebody buys an offering, seeking to co-create value with others, for themself, for the other, and/or for third parties. We buy in order to create value, with others or in relationship to them. And we see value-creating opportunities, which guide much of our buying. [Ramírez and Wallin 2000, p. 45]

An objective view of value might suggest the monetization of the product, e.g. the price tag. A subjective view of value has been extensively studied in economics, as ordered preferences in utility theory that an individual can make, but can’t be aggregated across a group. This interactive view of value gives a phenomenological spin, where a system is not independent of its environment.

2.3. The scope of science changes as the unobservable becomes observable

Sam Palmisano says that as the world gets “flatter”, smaller and more interconnected, the planet is becoming smarter. Smarter means that …

… digital and physical infrastructures of the world are converging.

Three advances in technology are driving this change.

  • The world is becoming instrumented: transistor technology is embedded in the mobile phones of 4 billion mobile subscribers today, and there will be 30 million RFID (Radio Frequency Identification) tags within 2 years.
  • The world is becoming interconnected: the Internet not only means 2 billion people connected person-to-person, but also the ability for instruments / devices to connect machine-to-machine.
  • Things are becoming more intelligent: since instrumented devices generate data that can be stored and analyzed, advanced analytics enables intelligence that can be translated into action — with nearly-continual real-time updates streaming from supercomputers. [Palmisano 2008]

In an exercise with “instrument, interconnected, intelligent” in the right column, consider what alternative antonyms for the left column might be. Here’s my attempt.

Pre-digital physical infrastructure . Converging digital and physical infrastructures
World as invisible or unobserved . Our world is becoming INSTRUMENTED

Analog / synchronous connections,

person-to-person and machine-to-machine

. Our world is becoming INTERCONNECTED
Things as dumb or unresponsive to interaction . Virtually all things, processes and ways of working are becoming INTELLIGENT

A world that is instrumented actively provides a continual stream of measurements. Without that active monitoring, those parts of the world are invisible or unobserved, as a tree falls in a forest with no one to hear it.

A world that is interconnected enables data and information to effortlessly flow and be applied in productive contexts, possibly beyond its originally designed purposes. Without reliable information interconnections, human beings serve as bridges: filling in contexts and storing subjective memories. While direct machine-to-machine interconnections are not a substitute for wisdom, the combination of observations from multiple devices can provide some consistency in objectivity.

Things that are intelligent can be programmed to selectively transmit varying sets of information to different receivers. Continual data streams encourage real-time alerts and action, when the receiving computer can process information at a rate faster than it arrives. In a data-rich environment, the constant arrival of fresh indicators eventually strains storage capacities, leading to archiving and/or data reduction procedures. A pre-digital infrastructure is unaware of its state, and has to be observed by something or someone outside itself.

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3. Natural scientists are researching resilience, panarchy, thresholds and regime shifts

Where are natural scientists conducting research complemented by the systems sciences? The domain of natural science is more mature than service science, so let me focus on one field that has maintained a strong interaction with the systems community: ecology. Some fields research where ecologists and service scientists may benefit from exchanges include:

  • 1. Resilience
  • 2. Cross-scale relations and panarchy
  • 3. Regime shifts and thresholds

Within ecology, there is a community focused on social ecological systems. They have developed an appreciation of social systems, and may not have encountered the perspective of service systems, yet.

3.1 Resilience

Ecosystem resilience has a history back into the 1970s [Holling 1973], with a rise in late 1990s associated with the Resilience Alliance [Petersen, Allen, Holling 1998]. This led to generalization across economic, ecological and social systems in an adaptive cycle:

There are three properties that shape the adaptive cycle and the future state of the system:

  • The inherent potential of a system that is available for change, since that potential determines the range of future options possible. This property can be thought of, loosely, as the "wealth" of a system.
  • The internal controllability of a system; that is the degree of connectedness between internal controlling variables and processes; a measure that reflects the degree of flexibility or rigidity of such controls, such as their sensitivity or not to perterbation.
  • The adaptive capacity; that is, the resilence of the system, a measure of its vulnerability to unexpected or unpredictable shocks. The property can be thought of as the opposite of the vulnerability of the system

These three properties -- wealth, controllability, and adaptive capacity -- are general ones, whether at the scale of the cell or the biosphere, the individual or the culture [Holling 2001]

In three dimensions, resilience is associated with potential and connectedness in an adaptive loop.

3.2 Cross-scale relations and panarchy

A system can be view at a variety of levels of scale. Changes at one scale might have impacts elsewhere at a different temporal or spatial scale.

Ecosystems are resilient when ecological interactions reinforce one another and dampen disruptions. Such situations may arise due to compensation when a species with an ecological function similar to another species increases in abundance as the other declines (Holling 1996), or as one species reduces the impact of a disruption on other species. However, different species operate at different temporal and spatial scales, as is clearly demonstrated by the scaling relationships that relate body size to ecological function (Peters 1983).

We define a scale as a range of spatial and temporal frequencies. This range of frequencies is defined by resolution below which faster and smaller frequencies are noise, and the extent above which slower and larger frequencies are background. Species that operate at the same scale interact strongly with one another, but the organization and context of these interactions are determined by the cross-scale organization of an ecosystem. Consequently, understanding interactions among species requires understanding how species interact within and across scales.

Many disturbance processes provide an ecological connection across scales. Contagious disturbance processes such as fire, disease, and insect outbreaks have the ability to propagate themselves across a landscape, which allows small-scale changes to drive larger-scale changes. [Peterson, Allen and Holling 1998]

The research into panarchy centers on cross-scale impacts.

The connected levels of of a panarchy are illustrated ....

One is the “revolt” connection, which can cause a critical change in one cycle to cascade up to a vulnerable stage in a larger and slower one.

The other is the “remember” connection which facilitates renewal by drawing on the potential that has been accumulated and stored in a larger, slower cycle. [Holling 2001]

3.3 Regime shifts and thresholds

The possibility of multiple stable states in ecology brings forward the opportunity for regime shifts.

Ecosystems are complex, adaptive systems that are characterized by historical dependency, nonlinear dynamics, threshold effects, multiple basins of attraction, and limited predictability (Levin 1999). Increasing evidence suggests that ecosystems often do not respond to gradual change in a smooth way (Gunderson & Pritchard 2002). Threshold effects with regime shifts from one basin of attraction to another have been documented for a range of ecosystems (see Thresholds Database on the Web site Passing a threshold marks a sudden change in feedbacks in the ecosystem, such that the trajectory of the system changes direction -- toward a different attractor. In some cases, crossing the threshold brings about a sudden, sharp, and dramatic change in the responding state variables, for example, the shift from clear to turbid water in lake systems (Carpenter 2003). In other cases, although the dynamics of the system have “flipped” from one attractor to another, the transition in the state variables is more gradual, such as the change from a grassy to a shrub dominated rangeland (Walker & Meyers 2004). [Folke, Carpenter, Walker et al. 2004, p. 559]

A threshold is a boundary in the transition from one stable state to another stable state.

What is a threshold?

A threshold is defined here as a point between alternate regimes in ecological or social-ecological systems. When a threshold along a controlling variable in a system is passed, the nature and extent of feedbacks change, such that there is a change in the direction in which the system moves. A shift occurs when internal processes of the system (rates of birth, mortality, growth, consumption, decomposition, leaching, etc.) have changed such that the variables that define the state of the system begin to change in a different direction, towards a different attractor. In some cases, crossing the threshold brings about a sudden, large and dramatic change in the responding variables, whilst in other cases the response in the state variables is continuous and more gradual. [Resilience Alliance and Santa Fe Institute 2004]

The Regime Shifts Database of large persistent changes in ecosystem services is at .

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4. Which frames might be brought with a systems approach?

Where might service scientists and natural scientists look for some common ground? As starting points, the legacy and advancements in seven frames may service as foundational frames:

  • 1. Socio-psychological, socio-technical, socio-ecological systems
  • 2. Collapse, resilience, sustainability, regeneration
  • 3. Complicatedness, complexity, gain
  • 4. Dialogue, conversation, language-action
  • 5. Power laws, scale-free networks
  • 6. Communities of practice, world disclosing
  • 7. Open standards, open source, reference models

In addition exchanges amongst scientists focused on service systems and natural systems, we should continue to look for opportunities for synergy, that may emerge as new knowledge.

4.1 Socio-psychological, socio-technical, socio-ecological systems

The socio-psychological, socio-technical and socio-ecological systems perspectives developed together, in a cascading sequence.

[... the] socio-psychological, the socio-technical and the socio-ecological perspectives ... emerged from each other in relation to changes taking place in the wider social environment. One could not have been forecast from the others. Though interdependent, each has its own focus. Many of the more complex projects require all three perspectives. [Trist & Murray 1997, p. 30]

The socio-psychological perspective grew out of World War II projects that included both the Tavistock Institute and the Tavistock Clinic.

[With ...] the socio-psychological [perspective ...] in Institute projects, the psychological forces are are directed towards the social field, wheres in the the Clinic, it is the other way around [with social forces directed toward the psychological field]. [....]

[Trist] was led to a concept of culture as a psycho-social process whcih could mediate between purely sociological and purely psychological frames of reference, a combination of which was needed in action research. [Trist and Murray 1997, pp. 30-31]

The socio-technical perspective was novel.

[The socio-technical perspective] originated in the early mining studies (Trist and Bamforth, 1951). Numerous projects have shown that the prevailing pattern of top-down bureaucracy is beginning to give way to an emergent nonlinear platform. The new paradigm is based on discovering the best match between the social and technical systems of an organization, since called the principle of joint optimization (Emery 1959). The notion of one narrowly skilled man doing one fractionated task was replaced by that of the multiskilled work group that could exchange assignments in a whole task system. This led to the further formualation by Emery (1967/Vol. III) of the second design principle, the redundancy of functions, as contrasted with the redundancy of parts. [Trist and Murray 1997, p. 31]

The socio-ecological perspective emerged in a response to an inability to manage complex interactive webs of relationship.

The importance of self-regulating organizations has ecome much greater in the context of the increasing levels of interdependence, complexity and uncertainty that characterize societies a the present time. Beyond certain thresholds the center/periphery model (Schon, 1971) no longer holds. There comes into being far more complex interactive webs of relationship that cannot be handled in this way. These changes in the wider environment prompted creation of the socio-ecological perspective ....

The coming of the information technologies and the signs of a transiton to a postindustrial society pose new problems related to emergent values such as cooperation and nurturance. Competition and dominance are becoming dysfunctional as the main drivers of post-industrial society. The value dilemmas created are reflected in the conflicts experienced by client organizations and in higher levels of stress for the individual. [Trist and Murray 1997, p. 32]

While each perspectives may be emphasized in different social engagement, they can be tied together into a whole.

The socio-ecological approach is linked to the socio-technical because of the critical importance of self-regulating organizations for turbulence reduction. It is further linked to the socio-psychological approach because of the need to reduce stress and prevent regression. [Trist and Murray 1997, p. 33]

Much of the work of the Tavistock Institute has become common wisdom in the disciplines of organization design and organization development. Despite the history going back into the 1950s, the relevance of this ideas to today's society is still strong.

4.2 Collapse, resilience, sustainability, regeneration

While sustainability is a popular idea in today's culture, it can be seen as a choice relative to other concepts.

A system that is not sustainable may decline, or come to a sudden collapse. Collapse can be seen in a sociopolitical context

Collapse ... is a political process. [....]

A society has collapsed when it displays a rapid, significant loss of an established level of sociopolitical complexity. [....]

To qualify as an instance of collapse a society must have been at, or developing toward, a level of complexity for more than one or two generations. [....]

The collapse, in turn, must be rapid - taking no more than a few decades — and must entail a substantial loss of sociopolitical structure. Losses that are less severe, or take longer to occur, are to be considered cases of weakness and decline.

Collapse is manifest in such things as:

  • a lower degree of stratification and social differentiation;
  • less economic and occupational specialization, of individuals, groups, and territories;
  • less centralized control; that is, less regulation and integration of diverse economic and political groups by elites;
  • less behavioral control and regimentation;
  • less investment in the epiphenomena of complexity, those elements that define the concept of ‘civilization’: monumental architecture, artistic and literary achievements, and the like;
  • less flow of information between individuals, between political and economic groups, and between a center and its periphery;
  • less sharing, trading, and redistribution of resources;
  • less overall coordination and organization of individuals and groups;
  • a smaller territory integrated within a single political unit.

[...] Collapse is a general process that is not restricted to any type of society or level of complexity [Tainter 1990].

Ecological resilience was described above, and can be contrasted with engineering resilience.

Resilience of a system has been defined in two different ways in the ecological literature. [....]

One definition focuses on efficiency, constancy, and predictability—all attributes at the core of engineers' desires for fail-safe design. The other focuses on persistence, change, and unpredictability—all attributes embraced and celebrated by biologists with an evolutionary perspective and by those who search for safe-fail designs.

The first definition, and the more traditional, concentrates on stability near an equilibrium steady state, where resistance to disturbance and speed of return to the equilibrium are used to measure the property (O'Neill et al., 1986; Pimm, 1984; Tilman and Downing, 1994). That view provides one of the foundations for economic theory as well and may be termed engineering resilience.

The second definition emphasizes conditions far from any equilibrium steady state, where instabilities can flip a system into another regime of behavior—that is, to another stability domain (Holling, 1973). In this case the measurement of resilience is the magnitude of disturbance that can be absorbed before the system changes its structure by changing the variables and processes that control behavior. We shall call this view ecological resilience (Walker et al., 1969). [....]

The two contrasting aspects of stability—essentially one that focuses on maintaining efficiency of function (engineering resilience) and one that focuses on maintaining existence of function (ecological resilience)—are so fundamental that they can become alternative paradigms whose devotees reflect traditions of a discipline or of an attitude more than of a reality of nature [Holling 1996, pp. 32-33].

From a more rigourous systems appreciation of sustainability, the emphasis shifts from managing just consumption to managing the contexts of production and consumption.

We sketch ... an understanding of sustainability that is more fundamental than mere exhortations to do such things as use public transportation and take colder showers. Sustainability entails management of systems and their contexts that is intensive and heavily knowledge-based. We will achive sustainability when it becomes a transparent outcome of managing the contexts of production and consumption rather than the consumption itself. If we shift our management emphases to managing from the context for whole ecosystem functions, rather than for resources, the cost of problem solving will diminish and the effectiveness of management greatly increase. When a manager gets the context right, the ecosystem does the rest. Because the material ecosystem supplies renewal resources and makes them renewable, we call our approach supply-side sustainability. [Allen, Tainter and Hoekstra 2003, p. 14]

Sustainability involves choice, and can be contrasted to resilience.

... when confronted with the term sustainability one should always ask, "Of what, for whom, for how long, and at what cost?" Incorporating these questions, we define sustainability as maintaining, or fostering the development of systemic contexts that produce the goods, services and amenities that people need or value, at an acceptable cost, for as long as they are needed or valued. Our concern, as we emphasize throughout, is context, not outputs.

It is important to distinguish sustainability from resiliency. Sustainability is the capacity to continue a desired condition or process, social or ecological. Resiliency is the ability of a system to adjust its configuration and function under disturbance. In social systems, resiliency can mean abandoning sustainability goals and the values that underlie them. Sustainability and resiliency can conflict. [pp. 26]

Social systems can be sustainable and resilient (social goals are flexible and in harmony with underlying ecological processes), unsustainable but resilient (the system adjusts to perturbations but not as people wish) or sustainable but not resilient (sustainability goals are feasible within narrow parameters but inflexible).

  • The first condition (sustainable and resilient) represents the mythical harmony that many writers impute (idealistically and often unrealistically) to tribal and peasant societies. Because such societies have dominated nearly all of human history, they may indeed, as a general class, be sustainable and resilient.
  • The second type (unsustainable but resilient) might describe contemporary industries that must reorganize to survive in a global economy.
  • The third case (sustainable but not resilient) describes societies that have diminished their own adaptability, which can arise from over-centralization [Allen, Tainter and Hoekstra 2003, pp. 26-27].

Regenerative systems can be contrasted to (non-sustainable) industrial systems. (note diagram on p. 26 on Google Books)

Industrial systems tend to apply strategies of concentration and subsidization; that is, energy and material flows are concentrated in small areas, and their operation is speed up by infusions of additional energy and materials. [....]

In contrast, regenerative systems tend to follow a strategy of dispersal, or spreading out over the landscape, combined with some degree of augmentation. [....]

Whatever the means used, sustainability requires that the basic processes not be exploited beyond their capacity for renewal. Whether by industrial or regenerative means, the landscape processes can only be used up to a point. If a higher volume of conversion is demanded than the sustainably productive capacities of the environment can provide, then the resource will become depleted. [Lyle 1996, pp. 28-29]

Lyle suggests a list of design strategies for regenerative systems" as a tentative effort to summarize the experience to date"

  • 1. Letting nature do the work
  • 2. Considering nature as both model and context
  • 3. Aggregating, not isolating
  • 4. Seeking optimum levels for multiple functions, not the maximum or minimum level for any one
  • 5. Matching technology to need
  • 6. Using information to replace power
  • 7. Providing multiple pathways
  • 8. Seeking common solutions to disparate problems
  • 9. Managing storage as a key to sustainability
  • 10. Shaping form to guide flow
  • 11. Shapring for to manifest process
  • 12. Prioritizing for sustainability [Lyle 1996, pp. 37-45]

Allen, Tainter and Hoekstra propose some principles of supply-side sustainability.

  • 1. Manage for productive systems rather than for their outputs
  • 2. Manage systems by managing their contexts
  • 3. Identify what dysfunctional systems lack and supply only that
  • 4. Deploy ecological processes to subsidize management efforts, rather than conversely
  • 5. Understand the problem of diminishing returns to problem solving [Allen, Tainter and Hoekstra 2003].

4.3 Complicatedness, complexity, gain

Complicatedness is differentiated from complexity in a sociopolitical context.

In a new vocabulary,we now identify structural elaboration as an increase in complicatedness, and distinguish it from elaboration of organization identified as an increase in complexity. We call the elaboration of organization a process of complexification, which leads to a complex system. The elaboration of structure we call a process of complication and it leads to a complicated system. The respective action verbs are to complexify and to complicate. Thus complexity is used hereafter in this paper to refer only to elaborate organization, except when we refer explicitly to usage in traditional or conventional terminology. By separating complicatedness from complexity, we are able to cast the modern human condition in terms of ancient and modern sociopolitical systems [Allen, Tainter and Hoekstra 1999, p. 407].

Gain in systems

The decline of high or low gain cycles leads to either extinction of some sort or a switch to the other type of gain.

High gain systems use readymade resources, and are so called because the return on effort of gathering the resource is high. Under a high gain regime, something other than the system at hand previously concentrated the resource. Therefore in the right situation the resource is ready for the taking without much need for refining what is gathered. But that right situation does not last because, once the hot spots of resource are dissipated, high gain systems either disappear or they must become low gain.

Low gain systems use lower quality resources. Under low gain the resource is so low quality as to require the system to extensively gather much raw material and then refine it. The process of refinement increases the quality of what has been captured so that it becomes high enough quality to be ready for use.

High and low gain systems both require fuel of high quality: high gain systems just take it, while low gain systems must make it.


In fact the duality of the resource as high or low depends not on the materiality of the situation, but upon how the system boundary is defined. A system is high gain if it is bounded so that refining the resource may be taken for granted because material exists already refined in the environment. Refining may be taken for granted because something in the environment refined the resources first (looted gold was refined by the previous owner, while seeds for eating were made by plants). But a high gain system redefined to be bounded as something larger may show low gain processes. In the larger conception the redefined system cannot take a high quality resource as a given and so must instead itself perform the refining of the resource as an active internal process. High and low gain thus becomes a matter of level of analysis. Hierarchy theory operates on questions of level of analysis, and so should be a useful framework here [Allen, Allen, Malek et. al. 2009, p. 586].

4.4 Dialogue, language-action, conversation

Design conversations include both generative and strategic dialogue.

The type of dialogue discuss heretofore is often called "generative," meaning that it generates a collective worldview.

... strategic dialogue focuses on specific issues and tasks and is applied in finding specific soltuions in organizational and social systems settings.

... it is important that before the design group engages in the substantive task of design, it involves itself in a generative dialogue.

This involvement will lead to the creation of collective consciousness, collective inquirty that focuses on the thoughts, values, and worldviews of the grouop and creates a flow of shared meaning, shared perceptions, a shared worldview, and a social milieu of friendship and fellowship. [Banathy 1996, p. 219]

The language-action perspective recognizes commitments, amongst other types of speech acts.

Searle distinguishes five kinds or ‘families’ of illocutionary acts along these dimensions of commitment, namely assertives, directives, commissives, declaratives, and expressives. [....]


The distinguishing characteristic of a directive is the commitment by the speaker, as he asks for the (future) performance of some action by the hearer. The propositional content of the directive expresses the action to be performed. [....] An imperative, where no illocutionary verb is explicitly mentioned, is normally understood as a directive. We may also distinguish actions such as requests, petitions, implorations, and orders as members of this class. [....]


Searle gives the name commissives to the particular class of acts in which the speaker becomes committed to the future performance of an action. As a speaker utters a commissive — a promise for example — he is also making the commitment that he has a serious intention to perform the action. [....] Verbs such as swear, commit, vow, and pledge in the present indicative are normally taken as commitments of this kind. [....]

All utterances are commitments according to this theory. In everyday use the word commitment is normally associated with what we call commissives, but this is an understanding we challenge. We instead assert:

  • It is unavoidable that commitments are expressed and listened to by the participants in a conversation.

What is peculiar about commissives is the double self referentiality of the commitment of the speaker, i.e., the expressed commitment to the intention to perform the act and the creation of the obligation to perform the act, as such. [Winograd and Flores 1986, p. 98]

A conversation for action is recognized in the context of other types of conversations.

We distinguish several additional kinds of conversation that go along with conversations for action (CfA):

  • conversation for clarification,
  • conversation for possibilities, and
  • conversation for orientation [Winograd 1986].

Conversations may be associated with accomplishments.


Individual speech acts as well as protocols for making and fulfilling commitments, individually, on teams, and in organizations.


Protocols for inventing new possible actions, often in response to threats or opportunities, and often followed by a declaration that the group will move toward one of the new possibilities. The declaration defines a new context and personal commitments to the next context. Managers, parents, and leaders make such declarations, often called “decisions.”


Revelations of concerns and worldviews. Some disclosures are willful, such as expressing an emotion or a concern. Others are revealed by our actions and practices, such as the aphorism “actions speak louder than words.” The skill of disclosing is intimately coupled with the skill of listening. Possibilities and disclosures create contexts for coordination. [Denning 2003]

4.5 Power laws, scale-free networks

While many laymen assume that nature tends to follow a bell curve, mathematicians know that some frequencies follow power laws.

In the past few decades, scientists have recognized that on occasion nature generates quantities that follow a power law distribution instead of a bell curve. Power laws are very different from ... bell curves .... First, a power law distribution does not have a peak. Rather, a histogram following a power law is a continuously decreasing curve, implying that many small events coexist with a few large events. [....] [The] distinguishing feature of a power law is not only that there are many small events but that the numerous tiny events coexist with a few large ones. These extraordinary large events are simply forbidden in a bell curve.

1 Bell curves have a decaying tail, which is a much faster decrease than that displayed by a power law. The exponential tail is responsible for the absence of the hubs. In comprison, power laws decay far more slowly, allowing for "rare events" such as the hubs. [Barabási 2002, pp. 67-68]

In analyzing the World Wide Web, it seems that power laws only partial describe the network.

... real networks are governed by two laws: growth and preferential attachment. Each network starts from a small nucleus and expands with the addition of new nodes. Then those new nodes, when deciding where to link, prefer the nodes that hvave more links. These laws representa a significant departure from earlier models, which assumed a fixed number of nodes that are randomly connected to each other. [...]

As the first model to explain the scale-free power laws seen in real networks, it quickly became know as the scale-free model. [Barabási 2002, pp. 86-87]

4.6 Communities of practice, world disclosing

Communities of practice are based on a social theory of learning.

... the primary focus of this theory is on learning as social participation. Participation here referes not just to local events of engagement in certain activities with certain people, but to a more encompassing process of being active participants in the practices of social communities and constructing identities in relation to these communities. Participating in a playground clique or in a work team, for instance, is both a kind of action and a form of belonging. Such participation shapes not only what we do, but also who we are and how we interpret what we do.

A social theory of learning must therefore integrate the components necessary to characterize social participation as a process of learning. These components, shown in Figure 0.1, include the following.

  • 1) Meaning: a way of talking about our (changing) ability -- individually and collectively -- to experience our life and world as meaningful.
  • 2) Practice: a way of talking about the shared historical and social resources, frameworks, and perspectives that can sustain mutual engagement in action.
  • 3) Community: a way of talking about the social configurations in which our enterprises are defined as worth pursuing and our participation is recognizable as competence.
  • 4) Identity: a way of talking about how learning changes who we are and creates personal histories of becoming in the context of our communities.

Clearly, these elements are deeply interconnected and mutually defining. [Wenger 1999, pp. 4-5]

The disclosing of new worlds rests on an Heideggerian philosophy, where everyday practices ground historical disclosing.

We call the general everyday kind of disclosive activity we have just described customary disclosing. We now turn to several ways in which disclosive activity can change the style of a disclosive space. We call this type of activity historical disclosing.

There are two kinds of skills required for historical disclosing. First, one has to be able to sense and hold on to disharmonies in one's current disclosive activity; second, one has to be able to change one's disclosive space on the basis of the disharmonious practices. [....]

Articulation, reconfiguration, and cross-appropriation are three different ways in which disclosive skills can work to bring about meaningful historical change of a disclosive space. All of these types of change are historical because people sense them as continuous with the past. The practices that newly become important are not unfamiliar. We contrast, then, our notion of historical change with discontinuous change. When, for instance, the conqueror imposes a whole new set of practices on the people or a people is dispersed and must adopt wholly new practices to survive, such a change is discontinuous and is beyond our range of interests. [Spinosa, Flores and Dreyfus 1999, p. 28]

4.7 Open standards, open source, reference models

The systems engineering community at INCOSE has developed SysML with the endorsement of the OMG.

The OMG systems Modeling Language (OMG SysML™) is a general-purpose graphical modeling language for specifying, analyzing, designing, and verifying complex systems that may include hardware, software, information, personnel, procedures, and facilities. In particular, the language provides graphical representations with a semantic foundation for modeling system requirements, behavior, structure, and parametrics, which is used to integrate with other engineering analysis models. SysML represents a subset of UML 2 with extensions needed to satisfy the requirements of the UML™ for Systems Engineering RFP as indicated in Figure 1. [Object Management Group 2008]

The design of cooperative work in software development teams is well-defined and supported by tools in an open source approach.

The Basic Elements

The basic elements ... are:

  • Work product: what is produced
  • Task: how to perform the work
  • Role: who performs the work
  • Process: used to define work breakdown and workflow
  • Guidance: templates, checklists, examples, guidelines, concepts, and so on.

These "basic elements" are the building blocks from which processes are composed.

Organizing Elements

The basic elements are organized using the following elements.


A practice is a documented approach to solving one or several commonly occurring problems. Practices are intended as "chunks" of process for adoption, enablement, and configuration. Practices are built from the basic elements described above.


From the end-user perspective, a configuration is a selection of method content to be published. Most configurations consist of a selection of practices plus some content to tie the practices together. The published configuration is often loosely referred to as a process website. [Eclipse Foundation 2010]

Frameworks enable coordination across ecologies of communities of practice. One example of an industry-driven framework is TOGAF (The Open Group Architecture Framework)

The Open Group Architecture Framework (TOGAF) is a framework — a detailed method and a set of supporting tools — for developing an enterprise architecture. It may be used freely by any organization wishing to develop an enterprise architecture for use within that organization (see Section 4.5.1).

TOGAF is developed and maintained by members of The Open Group, wor king within the Architecture Forum (refer to [The Open Group 2009]

Reference models enable a common vocabulary as a starting point. One leading example Within a domain, an

Ontario Public Service is in the business of providing services; it creates programs and delivers services to achieve the desired goals of government. When designing and managing a public sector enterprise, programs and services should drive organizational, process and resource planning and design, rather than vice versa. Figure 1-1 is a reference model which shows the relationships among jurisdictions, programs, services, organizations, processes and resources in a public sector enterprise. [Government of Ontario MGS 2010]

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5. Learning and knowing can be encouraged through multiple perspectives dialectics

"The systems approach begins when you first see the world through the eyes of another". [Churchman 1968, p. 231]

The systems approach has recognized five ways of knowing through the design of inquiring systems.

An Inquiry System, or IS for short, is a system of interrelated components for producing knowledge on a problem or issue of importance. [Mitroff and Linstone 1993]

The design of the 56th Annual Meeting of the ISSS is as a Singerian inquiring system, i.e. the "fifth way" of knowing of multiple perspectives dialectics.

6. Come share in the learning at ISSS San Jose 2012, in California

See .

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Ackoff, Russell L., and Fred E. Emery. 1972. On purposeful systems. Aldine-Atherton.

Ackoff, Russell L. 1981. Creating the Corporate Future: Plan or Be Planned For. John Wiley and Sons.

Allen, Timothy F. H., Joseph A. Tainter, and Thomas W. Hoekstra. 1999. “Supply-side sustainability.” Systems Research and Behavioral Science 16 (5): 403-427. doi:10.1002/(SICI)1099-1743(199909/10)16:5<403::AID-SRES335>3.0.CO;2-R.<403::AID-SRES335>3.0.CO;2-R.

Allen, Timothy F. H., Joseph A Tainter, and Thomas W. Hoekstra. 2003. Supply-side sustainability. New York: Columbia Univ Press.

Allen, Timothy F. H., Peter C. Allen, Amy Malek, John Flynn, and Michael Flynn. 2009. “Confronting economic profit with hierarchy theory: The concept of gain in ecology.” Systems Research and Behavioral Science 26 (5): 583-599. doi:10.1002/sres.998.

Banathy, Bela H. 1996. Designing social systems in a changing world. Springer.

Barabási, Albert-László. 2002. Linked: The New Science of Networks. Cambridge, MA: Basic Books.

Bateson, Gregory. 1972. The Logical Categories of Learning and Communication. In Steps to an ecology of mind, 279-308. Northvale, NJ: Jason Aronson.

Boulding, Kenneth E. 1956. “General Systems Theory-The Skeleton of Science.” Management Science 2 (3): 197-208. doi:10.1287/mnsc.2.3.197.

Checkland, Peter. 1981. Systems thinking, systems practice. Wiley.

Churchman, C. West. 1968. The systems approach. Delacorte Press.

Demirkan, Haluk, James C. Spohrer, and Vikas Krishna, eds. 2011. The Science of Service Systems. Service Science: Research and Innovations in the Service Economy. Springer.

Denning, Peter J. 2003. “Accomplishment.” Communications of the ACM 46 (7): 19–23. doi:10.1145/792704.792722.

Eclipse Foundation. 2010. Open Unified Process -- Getting Started: Basic Process Concepts.

Folke, Carl, Steve Carpenter, Brian Walker, Marten Scheffer, Thomas Elmqvist, Lance Gunderson, and C.S. Holling. 2004. “Regime Shifts, Resilience, and Biodiversity in Ecosystem Management.” Annual Review of Ecology, Evolution, and Systematics 35 (1) (December): 557-581. doi:10.1146/annurev.ecolsys.35.021103.105711.

Government of Ontario Ministry of Government Services. 2010. Defining Programs and Services in the Ontario Public Service. In Information Technology Standards. Architecture Standards GO-ITS 56.1 version 1.3 Appendix. Queen’s Printer for Ontario.

Hall, Arthur David. 1962. A methodology for systems engineering. Van Nostrand.

Hammond, Debora. 2003. The science of synthesis: exploring the social implications of general systems theory. University Press of Colorado.

Holling, C S. 1973. “Resilience and Stability of Ecological Systems.” Annual Review of Ecology and Systematics 4 (1) (November): 1-23. doi:10.1146/

Holling, C.S. 1996. Engineering Resilience versus Ecological Resilience. In Engineering within Ecological Constraints, ed. Peter C. Schulze, 31-44. National Academies Press.

Holling, C. S. 2001. “Understanding the Complexity of Economic, Ecological, and Social Systems.” Ecosystems 4 (5): 390-405. doi:10.1007/s10021-001-0101-5.

IBM. 2010. The World’s 4 Trillion Dollar Challenge: Using a system-of-systems approach to build a smarter planet. Institute for Business Value.

IfM, and IBM. 2008. Succeeding through Service Innovation: A Service Perspective for Education, Research, Business and Government. Cambridge, UK: University of Cambridge Institute for Manufacturing.

Ing, David, Minna Takala, and Ian Simmonds. 2003. Anticipating organizational competences for development through the disclosing of ignorance. In Proceedings of the 47th Annual Meeting of the International Society for the System Sciences. Hersonissos, Crete.

Lyle, John T. 1996. Regenerative Design for Sustainable Development. John Wiley and Sons.

Mitroff, Ian I., and Harold A. Linstone. 1993. The unbounded mind: Breaking the chains of traditional business thinking. New York: Oxford University Press.

Object Management Group. 2008. What is OMG SysML?

Palmisano, Samuel J. 2008. A Smarter Planet: The Next Leadership Agenda. Web audio. Council on Foreign Relations. New York, NY, November 6.

Peterson, Garry, Craig R. Allen, and C. S. Holling. 1998. “Ecological Resilience, Biodiversity, and Scale.” Ecosystems 1 (1): 6-18. doi:10.1007/s100219900002.

Ramírez, Rafael, and Johan Wallin. 2000. Prime movers: define your business or have someone define it against you. Chichester, England: Wiley.

Resilience Alliance, and Santa Fe Institute. 2004. Thresholds and alternate states in ecological and social-ecological systems. Resilience Alliance.

Schwab, Klaus. 2010. Davos 2011. Web Video. December 15.

Schwab, Klaus. 2011. “Survival in the Age of Complexity.” The Telegraph, July 13.

Spinosa, Charles, Fernando Flores, and Hubert L. Dreyfus. 1999. Disclosing new worlds: Entrepreneurship, Democratic Action, and the Cultivation of Solidarity. MIT Press.

Spohrer, James C., and Paul P. Maglio. 2010. Toward a Science of Service Systems: Value and Symbols. In Service Science: Research and Innovations in the Service Economy, ed. Paul P. Maglio, Cheryl A. Kieliszewski, and James C. Spohrer, 157-194. 10.1007/978-1-4419-1628-0_9. Boston, MA: Springer.

Tainter, Joseph A. 1990. The Collapse of Complex Societies. Cambridge University Press.

The Open Group. 2009. TOGAF Version 9. Van Haren Publishing.

Tien, James M. 2008. “Services: A System’s Perspective.” IEEE Systems Journal 2 (1): 146-157. doi:10.1109/JSYST.2008.917075.

Trist, Eric L., and Hugh Murray. 1997. Historical Overview: The Foundation and Development of the Tavistock Institute to 1989. In The Social Engagement of Social Science: The socio-ecological perspective, ed. Eric L. Trist, Frederick E. Emery, and Hugh Murray, 3:1-35. Philadelphia: University of Pennsylvania Press.

Wenger, Etienne. 1999. Communities of practice: learning, meaning and identity. Cambridge, UK: Cambridge University Press.

Winograd, Terry, and Fernando Flores. 1986. Understanding Computers and Cognition: A New Foundation for Design. Norwood, NJ: Ablex.

Winograd, Terry. 1986. A language/action perspective on the design of cooperative work. In Proceedings of the 1986 ACM conference on Computer-supported cooperative work, 203-220. Austin, Texas: ACM. doi:10.1145/637069.637096.

Witte, M. H, A. Kerwin, and C. L Witte. 1998. Curriculum on medical and other ignorance: shifting paradigms on learning and discovery. In Memory distortions and their prevention, ed. Deborah L Best and Margaret J. Intons-Peterson, 125–156. Psychology Press.

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2011/07/22 ISSS Incoming Presidential Address