Narrow Results

This paper develops a computer-aided process simulation model (CPSM) to navigate value chain reconfiguration. The model uses a three-layered methodology incorporating the principle of knowledge-integrated traceability (KIT) to create more efficient performance measures and provides a rigorous and stepwise clustered module structure that will act as a guideline for all entities decision makers are involved. The model is based on three kinds of mature toolsets variable. First, an in-depth interview of a group of experts makes the BSC (Balanced Scorecard) KIT model along with AHP (Analytic Hierarchy Process) technique into an integrated AHP-BSC structure. Second, internal validation of core propositions during CPSM development is then used to construct an account both qualitative and quantitative decision factors in the best delivery causality diagram of theory-building mode. Defining the KIT of toolset variables into two specific themes allows a practical hierarchy for AHP-BSC structure to be evaluated without excessive computation barriers, and the systems thinking archetype of strategic activities in the ARIS-EPCs (Architecture of Integrated Information System/extending Event-driven Process Chains) architecture delivers the validity and reliability of research methodology as validation model of CPSM development. Third, the hybrid ST-ARIS (System Thinking) simulation model is constructed based on the feasibility test of relevant decision factors whether or not KPI (Key Performance Indicator) could be measured. The reconfiguration provides new insights for contributing to the foundations to link the process capability of the value chain with the three-layered methodology, and emphasises the CPSM development by highlighting a specific approach associated with KIT.

This paper appraises the criticism that "Knowledge Management (KM) is little more than re-packaged Information Management (IM)" through analysis of the relationships and inconsistencies between IM and KM. This is supported by a case study of the loss of an UK Royal Air Force aircraft known as 'Nimrod' as reported in the Haddon-Cave Independent Review.

The first part discusses the research methodology adopted and analyses the literature including the theoretical characteristics and practical aspects of IM and KM. This is supported by logical models and relationship tables for comparison. The second part develops an analytical framework by applying evaluation criteria, based on principles for Through Life Management of information, to a case study to address the statement that "information is inadequate without knowledge."

The logical models and case study insertions uncovered important conclusions: (1) KM is frequently confused with IM and reliance on IM only can sometimes result in a disaster; (2) it is imperative to understand the distinctions between IM and KM as "management of knowledge" is concerned with socio-technical, hence human, aspects to a greater extent than IM; (3) IM should be considered as a prerequisite to engaging KM; and (4) KM should be perceived as the creation and management of knowledge as a human centred attribute that involves a learning and transformation process.

This paper systematically applies the derived logical models and analysis framework to a case study to better understand and illustrate the implications of Through Life Management of information and knowledge.

Living within the limits imposed by a finite earth may be the predominant challenge of the 21st century; however there is no agreement on what this means economically or politically. Continually increasing population and per capita consumption within a finite environment is a biologic impossibility. Today many of nature's resources are being harvested at rates where growth is uneconomic and damaging to future production.

This paper explores linkages between economics, society and nature as complex adaptive systems in a world of uncertainty. To understand that these self organising systems exist in equilibrium, dependent on feedback loops, is to understand that as humanity destroys system equilibrium we push the entire system to the edge of criticality and perhaps chaos. Consequences of criticality and chaos theory are now thought to follow power laws; wherein the size of any single system disruption is impossible to predict, especially when inter-relationships with other systems are not understood. Understanding the biosphere from a holistic perspective is critical when considering priorities and making wise choices.

Thoughts of some environmental thinkers are reviewed for a perspective on the meaning of true sustainability, where it may lead and how we must redesign human systems to adapt to a sustainable world. The authors believe holism exists; that similarities with other fields of study exist in the environmental issues of today; and, that ideas and solutions may be also found in unexpected places. Although no recommendations are made it is hoped that interest is stimulated in answering the question when are we going to act collectively to address some of the present day myriad issues.

Global warming is one of the most pressing issues facing our world today. Much has already been written on the urgency with which we must reduce greenhouse gas emissions, pull carbon out of the air, and redesign our social-environmental systems towards a new way of doing business that is restorative and regenerative in nature. What has been lacking is an understanding of real, workable technologies and practices to get us there…

Many scientific reports have warned about the catastrophic consequences of unchecked climate change, with the latest international report calling for emissions of climate pollutants to reach net zero by around 2050 (IPCC, 2018). Limiting warming to 1.5°C could save more than 100 million people from water shortages, as many as 2 billion people from dangerous heatwaves, and the majority of species from climate change extinction risks (IPCC, 2018; Warren et al., 2018). The actions taken to achieve these climate outcomes would generate benefits of more than $20 trillion while easing global economic inequality (Burke et al., 2018). Scientists make it clear that it is physically possible to meet these goals using today’s technologies (Holz et al., 2018). Yet emissions of climate pollutants continue to grow, reaching a new record high in 2018 (Jackson et al., 2018). Clearly, scientific evidence has failed to spark needed climate action. The question now is: what can?…

The 2030 UN Agenda provides a list of 17 Sustainable Development Goals (SDGs). Typically, SDGs are viewed as non-hierarchical, if not standalone, objectives. Our aim is to represent the structure of multilayered relationships among the SDGs, where possible assigning influence links in order to configure a systems thinking view. We develop a Causal Loop Diagram (CLD) of the SDGs, which illuminates multiple linkages among these global targets and begins to address measurement issues in pursuing the Agenda. To close the system and further operationalize SDG interrelationships, we propose the addition of one further goal — population growth limits — using a system dynamics modeling analysis. Our main contribution supports the systems view that SDGs constitute a highly-interconnected network. While acknowledging that the articulation and initial efforts toward implementing the SDGs have themselves been major steps forward, we further posit that consideration of their systemic interconnectedness is indispensable for increasing the chances of achieving sustainability on planet Earth.

The human capital required to develop and sustain competitive advantage in Artificial Intelligence (AI) is in short supply globally. In this context, Singapore’s Artificial Intelligence Apprenticeship Program (AIAP) is a leading example of a public–private partnership that has fostered the growth of an indigenous talent pool in Singapore. We aim to elicit the systemic structure of AIAP in the form of a Causal Loop Diagram (CLD), and to derive actionable insights to support policymakers, managers, and researchers who are interested in the development of AI talents. Our CLD reflects the diversity of factors and their interactions that need to come together to make AIAP work. The design of AIAP reflects a pragmatic partnership between stakeholders who are interested in national competitiveness, making their own industries and firms more competitive, furthering the use of AI, and developing careers in a field with promising future prospects. To our knowledge, this is the first study of AIAP from a systems thinking viewpoint. The shared understanding of stakeholders reflected in the CLD provides insight for policymakers who seek to develop national competitiveness through investment in human capital for AI.

We introduce some core principles related to systems thinking: interaction, establishment of systems through organization and self-organization (emergence), and the constructivist role of the observer including the use of language. It is not effective to deal with systemic properties in a non-systemic way, by adopting a reductionist way of thinking, i.e., when properties acquired by systems are considered as properties possessed by objects. We consider the reduced language adopted in consumer societies as functional to maintain consumerist attitude. In consumer societies, language is suitable for maintaining people in the role of consumers with a limited ability to design and create. In this context freedom is intended as freedom of choice. To counteract this reduced language, we propose the diffusion of suitable games, cartoons, comics and pictures, images, concepts and words which can enrich everyday language, especially that of young people, and provide an effective way for inducing some elementary aspects of systems thinking in everyday life. The purpose is to have a language to design and develop things and not merely to select from what is already available. We list a number of proposals for the design of such games, stories and pictures.

This chapter highlights the impact and manageability of rapid, constantly/ continuously and unique changes taking place in humanity that are affecting the existence individuals, as well as all categories of human organizations. It has been observed that the traditional Newtonian mindset, and its associated reductionist hypothesis and design paradigm that have served humanity ‘well’ are manifesting their limits/constraints, vulnerability and disparities. The crux of the issue is escalating complexity density, incoherency, greater mismatch among current thinking, principles, values, structure, dynamic, and hierarchical dominance, limited predictability, and the overall changing ‘reality’.

Vividly, order and linearity are not the only inherent attributes of humanity. Consequently, the significance, appropriateness and exploration of certain properties of complexity theory are introduced, partially to better identify, analyze, comprehend and manage the accelerating gaps of inconsistency — in particular, to nurture a new mindset. Arising from the new mindset, human organizations/systems are confirmed as intrinsic composite complex adaptive systems (composite CAS, nonlinear adaptive dynamical systems) comprising human beings/agents that are CAS. In this respect, leadership, governance, management, and strategic approaches adopted by all human organizations must be redefined.

Concurrently, a special focus on intelligence (and its associated consciousness), the first inherent strengths of all human agents, and its role as the key latent impetus/driver, is vital. This recognition indicates that a change in era is inevitable. Humanity is entering the new intelligence era — the core of the knowledge-intensive and complexity-centric period. Overall, an integrated intelligence/consciousness-centric, complexity-centric and network-centric approach is essential. It adopts a complexity-intelligence-centric path that focuses on the optimization of all intense intrinsic intelligence/consciousness sources (human thinking systems), better exploitation of the co-existence of order and complexity, and integration of networks in human organizations — (certain spaces of complexity must be better utilized, coherency of network of networks must be achieved, and preparation for punctuation point must be elevated).

The new holistic (multi-dimensional) strategy of the intelligent organization theory (IO theory) is the complexity-intelligence strategy, and the new mission focuses on the new intelligence advantage.

This chapter is an introduction to complexity theory (encompassing chaos — a subset of complexity), a nascent domain, although, it possesses a historical root. Some fundamental properties of chaos/complexity (including complexity mindset, nonlinearity, interconnectedness, interdependency, far-from-equilibrium, butterfly effect, determinism/in-determinism, unpredictability, bifurcation, deterministic chaotic dynamic, complex dynamic, complex adaptive dynamic, dissipation, basin of attraction, attractor, chaotic attractor, strange attractor, phase space, rugged landscape, red queen race, holism, self-organization, self-transcending constructions, scale invariance, historical dependency, constructionist hypothesis and emergence), and its development are briefly examined. In particular, the similarities (sensitive dependence on initial conditions, unpredictability) and differences between deterministic chaotic systems (DCS) and complex adaptive systems (CAS) are analyzed. The edge of emergence (2^nd critical value, a new concept) is also conceived to provide a more comprehensive explanation of the complex adaptive dynamic (CAD) and emergence. Subsequently, a simplified system spectrum is introduced to illustrate the attributes, and summarize the relationships of the various categories of common systems.

Next, the recognition that human organizations are nonlinear living systems (high finite dimensionality CAS) with adaptive and thinking agents is examined. This new comprehension indicates that a re-calibration in thinking is essential. In the human world, high levels of human intelligence/consciousness (the latent impetus that is fundamentally stability-centric) drives a redefined human adaptive and evolution dynamic encompassing better potentials of self-organization or self-transcending constructions, autocatalysis, circular causation, localized spaces/networks, hysteresis, futuristic, and emergent of new order (involving a multi-layer structure and dynamic) — vividly indicating that intelligence/consciousness-centric is extremely vital. Simultaneously, complexity associated properties/characteristics in human organizations must be better scrutinized and exploited — that is, establishing appropriate complexity-intelligence linkages is a significant necessity. In this respect, nurturing of the intelligence mindset and developing the associated paradigmatic shift is inevitable.

A distinct attempt (the basic strategic approach) of the new intelligence mindset is to organize around human intrinsic intelligence — intense intelligence-intelligence linkages that exploits human intelligence/consciousness sources individually and collectively by focusing on intelligence/consciousness-centricity, complexity-centricity, network-centricity, complexity-intelligence linkages, collective intelligence, org-consciousness, complex networks, spaces of complexity (better risk management <=> new opportunities <=> higher sustainability) and prepares for punctuation points (better crisis management <=> collectively more intelligent <=> higher resilience/sustainability) concurrently — illustrating the significance of self-organizing capability and emergence-intelligence capacity. The conceptual development introduced will serve as the basic foundation of the intelligent organization (IO) theory.

The chapter concludes the book by illustrating the potential of extending the boundaries of the intelligence mindset and its space of innovation and creativity. Some theories that could be integrated subsequently are mentioned briefly. In addition, a holistic view (new knowledge creation) of the intelligence paradigm, the complexity-intelligence strategy, and the intelligent organization theory is summarized through recollecting and amalgamating the various normative attributes, concepts, perspectives and strategies analyzed. Organizing around intelligence (including intelligence/consciousness management, complexity management and network management), and the integrated deliberate and emergent strategy (exploitation of the co-existence of order and complexity) are the (holistic) fundamental strategies that must be exploited in the present environment. Due to the current high complexity and nonlinearity, this paradigmatic shift is apparently beneficial. As indicated earlier, properties of complex adaptive systems and the complex adaptive dynamic must be better comprehended and exploited by all human organizations to elevate competitiveness, resilience and sustainability.

In summary, the intelligent organization theory introduced in this book contains concepts and ideas (including intelligence/consciousness-centricity, complexity-centricity, network-centricity, intelligence-intelligence linkage, complexity-intelligence linkage, self-organizing capacity, emergence-intelligence capacity, coherency, synergy, constructionist effect and mental cohesion) that are more holistic, integrative, and accurate manifestations of humanity and its organizations and agents. Thus, it is highly critical for the leadership, governance, strategy, and management in rapidly changing environment. Primarily, it is a new significant complexity-intelligence-relational/network domain (a more inherent aspect of nature and this universe) that must be better comprehended and exploited by all human organizations. As indicated, the complexity-intelligence strategy of the intelligent organization theory encompasses numerous components, including organizing around intelligence, integrated deliberate and emergent strategy, general information theory, 3C-OK framework, intelligent person model, intelligent multi-layer structure model, intelligence leadership theory/strategy, intelligence governance theory/strategy, and relativistic complexity.

Fundamentally, the new thinking emphasizes the significance and linkages of the human intelligence/consciousness sources, and stabilitycentricity at all levels (agent-centric, network-centric and org-centric), co-existence of order and complexity, and the attributes of swift information decoders, smarter evolvers and emergent strategists. The strategies and models/frameworks of the intelligent organization theory that focus on structuring, nurturing, leading, and governing/managing of highly intelligent human organizations (iCAS) that are orchestrated by the highly intelligent complex adaptive dynamic (iCAD) are briefly recaptured. Ultimately, it is the intention of the author that an omniscient understanding of this book will instill in leaders and actors the new critical intelligence advantage.

This chapter provides guidance for solving practical, high-level management and policy challenges in sustainability and disaster resilience. These two fields must be considered together so that they do not work at cross-purposes. Sustainability is framed in a positive and useful way that transcends shallow and self-serving treatments that are all too common. Although sustainability is a multi-faceted problem, climate change is the focus because it is globally important and because it is particularly troublesome due to its global and long-term scale. The discussion on sustainability highlights the challenge of extreme uncertainty. Knowledge of system complexity is necessary for understanding and contending with extreme uncertainty. Thus, this chapter summarizes some fundamental knowledge and draws from it recommendations for decision-making. An example illustrates the suggested approach and provides additional insight. Complex systems are hard to understand and no course of action is guaranteed to be successful. However, without systems thinking, failure is almost assured. The recommendations in this chapter, although not infallible, will help find effective ways to intervene in societal systems to meet stated objectives while avoiding unintended consequences.

In this chapter we are looking critically at our capitalist market system, or at least at the models we might use to predict market behaviour and make market decisions, and wondering what happened to the main player — the consumer — in the system. Indeed, the consumer, in most models is marginalized or dehumanized if considered at all. A revisit to both the logic and the ideals of capitalism of Adam Smith and others is undertaken. Creatively reengineering the market system is the task addressed. This requires an understanding of what constitutes a creative process.

Two kinds of applications of game theory were outlined in [Aumann (2008)]. In one we get insight into an interactive situation and, in the other, game theory tells us what to do. Aumann calls the second kind of applications, game engineering. Organisational systems gurus, Russell Ackoff and Sheldon Rovin explain how to outsmart bureaucracies in their celebrated work ‘Beating the System’ [Ackoff and Rovin (2005)]. What is common between game engineering and beating the system is creativity. We apply this understanding to games played in the market place. This leads us to consider thought experiments, social dialogues, and models that stipulate the rightful place for the consumers as main players.