Showing papers on "Complex adaptive system published in 2006"

Studying Complex Adaptive Systems

Abstract: Complex adaptive systems (cas) – systems that involve many components that adapt or learn as they interact – are at the heart of important contemporary problems. The study of cas poses unique challenges: Some of our most powerful mathematical tools, particularly methods involving fixed points, attractors, and the like, are of limited help in understanding the development of cas. This paper suggests ways to modify research methods and tools, with an emphasis on the role of computer-based models, to increase our understanding of cas.

Agent-based computational economics : A constructive approach to economic theory

Abstract: Economies are complicated systems encompassing micro behaviors, interaction patterns, and global regularities. Whether partial or general in scope, studies of economic systems must consider how to handle difficult real-world aspects such as asymmetric information, imperfect competition, strategic interaction, collective learning, and the possibility of multiple equilibria. Recent advances in analytical and computational tools are permitting new approaches to the quantitative study of these aspects. One such approach is Agent-based Computational Economics (ACE) , the computational study of economic processes modeled as dynamic systems of interacting agents. This chapter explores the potential advantages and disadvantages of ACE for the study of economic systems. General points are concretely illustrated using an ACE model of a two-sector decentralized market economy. Six issues are highlighted: Constructive understanding of production, pricing, and trade processes; the essential primacy of survival; strategic rivalry and market power; behavioral uncertainty and learning; the role of conventions and organizations; and the complex interactions among structural attributes, institutional arrangements, and behavioral dispositions.

Organizations as complex adaptive systems: Implications of Complexity Theory for leadership research

Abstract: This article contrasts the assumptions of General Systems Theory, the framework for much prior leadership research, with those of Complexity Theory, to further develop the latter's implications for the definition of leadership and the leadership process. We propose that leadership in a Complex Adaptive System (CAS) may affect the organization indirectly, through the mediating variables of organizational identity and social movements. A rudimentary model of leadership in a CAS is presented. We then outline two non-linear methodologies, dynamic systems simulation and artificial neural networks, as appropriate to enable development and testing of a model leadership under the assumptions of Complexity Theory.

From Community-Based Resource Management to Complex Systems: The Scale Issue and Marine Commons

Abstract: Most research in the area of common property (common-pool) resources in the last 2-3 decades sought the simplicity of community-based resource management cases to develop theory. This was mainly because of the relative ease of observing processes of self-governance in simple cases. However, this creates a problem. Whether the findings of small- scale, community-based commons can be scaled up to generalize about regional and global commons is much debated. Even though some of the principles from community-based studies are likely relevant across scale, new and different principles may also come into play at different levels. Cross-scale institutions (such as institutions of co- management) have something in common: they provide ways to deal with complex adaptive systems. They all pertain to various aspects of complexity, such as selforganizatio n, uncertainty, and resilience, and deal with the challenges of scale. Communities themselves can be seen as complex systems -- embedded in larger complex systems. Thus, community-based resource management needs to deal with cross-scale governance and external drivers of change, as I illustrate with examples of marine commons.

Inter-Organizational Coordination in Extreme Events: The World Trade Center Attacks, September 11, 2001

Abstract: This paper addresses the problem of inter-organizational coordination in response to extreme events. Extreme events require coordinated action among multiple actors across many jurisdictions under conditions of urgent stress, heavy demand and tight time constraints. The problem is socio-technical in that the capacity for inter-organizational coordination depends upon the technical structure and performance of the information systems that support decision making among the participating organizations. Interactions among human managers, computers and organizations under suddenly altered conditions of operation are complex and not well understood. Yet, coordinating response operations to extreme events is an extraordinarily complex task for public and nonprofit managers. This paper will analyze the interactions among public, private and nonprofit organizations that evolved in response to the 11 September 2001 attacks, examining the relationships among organizations in terms of timely access to information and types of supporting infrastructure. The performance of the inter-organizational system is examined in the context of the events of 11 September 2001 from the theoretical perspective of complex adaptive systems. A model of auto-adaptation is proposed for implementation to improve inter- organizational performance in extreme events. This model is based on the concept of individual, organizational and collective learning in environments exposed to recurring risk, guided by a shared goal. Such a model requires public investment in the development of an information infrastructure that can support the intense demand for communication, information search, exchange and feedback that characterizes an auto-adaptive system.

Matching Social and Ecological Systems in Complex Ocean Fisheries

Abstract: This paper considers ocean fisheries as complex adaptive systems and addresses the question of how human institutions might be best matched to their structure and function. Ocean ecosystems operate at multiple scales, but the management of fisheries tends to be aimed at a single species considered at a single broad scale. The paper argues that this mismatch of ecological and management scale makes it difficult to address the fine-scale aspects of ocean ecosystems, and leads to fishing rights and strategies that tend to erode the underlying structure of populations and the system itself. A successful transition to ecosystem-based management will require institutions better able to economize on the acquisition of feedback about the impact of human activities. This is likely to be achieved by multiscale institutions whose organization mirrors the spatial organization of the ecosystem and whose communications occur through a polycentric network. Better feedback will allow the exploration of fine-scale science and the employment of fine-scale fishing restraints, better adapted to the behavior of fish and habitat. The scale and scope of individual fishing rights also needs to be congruent with the spatial structure of the ecosystem. Place-based rights can be expected to create a longer private planning horizon as well as stronger incentives for the private and public acquisition of system relevant knowledge.

On complex adaptive systems and agent-based modelling for improving decision-making in manufacturing and logistics settings: Experiences from a packaging company

Abstract: Purpose – This paper aims to contribute to the tactical and operational decision making of manufacturing and logistics operations by providing novel insights into modelling and simulation, based on complex adaptive systems (CAS).Design/methodology/approach – The research approach is theoretically based on CAS with agent‐based modelling (ABM) as the implementation method. A case study is presented where an agent‐based model has contributed to increased understanding and precision in decision making at a packaging company in the UK.Findings – The results suggest that ABM provides decision‐makers with robust and accurate “what‐if” scenarios of the dynamic interplay among several business functions. These scenarios can guide managers in the process of moving from policy space to performance space, i.e. concerning priorities of improvement efforts and choices of production/manufacturing policies, warehouse policies, customer service policies and logistics policies. Furthermore, it is found that ABM can include...

Emergent States in Virtual Teams: A Complex Adaptive Systems Perspective:

Abstract: Research on virtual teams (VTs) has proliferated in the last decades. However, few clear and consistent theoretical attempts to integrate the literature on VTs in a systemic way have emerged. This paper uses the complex adaptive systems (CAS) perspective to integrate the literature on emergent states in VTs. According to this general framework, VT effectiveness depends on the interaction between three levels of dynamics: local, global and contextual. Team cognition, trust, cohesion and conflict are described as states that emerge from the interactions among the VT members and as parts of global dynamics, they impact on VT effectiveness, and in the same time they are influenced by the outcomes of the VT. The insights on this bidirectional causality as well as other benefits of using the CAS framework to improve our understanding of VTs are discussed in the paper. It also provides an overview of artificial simulation models as well as simulation results concerning the emergence of the four states described in the CAS framework and discusses several ways to improve the accuracy of the simulation models using empirical data collected in real VTs.

Nonlinear pedagogy: a constraints-led framework for understanding emergence of game play and movement skills.

Abstract: Team sport competition can be characterized as a complex adaptive system in which concepts from nonlinear dynamics can provide a sound theoretical framework to understand emergent behavior such as movement coordination and decision making in game play. Nonlinear Pedagogy is presented as a methodology for games teaching, capturing how phenomena such as movement variability, self-organization, emergent decision making, and symmetry-breaking occur as a consequence of interactions between agent-agent and agent-environment constraints. Empirical data from studies of basketball free-throw shooting and dribbling are used as task vehicles to exemplify how nonlinear phenomena characterize game play in sport. In this paper we survey the implications of these data for Nonlinear Pedagogy, focusing particularly on the manipulation of constraints in team game settings. The data and theoretical modeling presented in this paper provide a rationale in nonlinear dynamics for the efficacy of a prominent model of game play teaching, Teaching Games for Understanding approach.

Complexity, simplicity, and epidemiology

Abstract: It should be stressed that although many phenomena are complex, 15 the concept of ‘complexity’ is more specific. Complexity is the study of complex adaptive systems. These have been defined as ‘a collection of individual agents with freedom to act in ways that are not always totally predictable, and whose actions are interconnected so that one agent’s actions changes the context for other agents’. 16 Such systems include living cells, the brain, the immune system, the financial markets, ecosystems, and human populations. They are complex in the sense that there are a great many apparently independent agents interacting with each other, but the richness of these interactions allows the system as a whole to undergo self-organization. 1 They are also characterized as involving non-linearity and feedback loops in which small changes can have striking effects that cannot be understood simply by analysing the individual components. 17 The whole is more than the sum of its (reductionist) parts. Such complex systems can exist on a number of different levels from the subatomic through to the individual level, the population level, and beyond. 18 The most striking example of a complex self-organizing system is life itself, not only in terms of individual organisms but also in evolutionary terms—organisms adapt to each other through evolution into a finely tuned ecosystem. Similarly, various populations have evolved traditional ways of life that are now responding to the changes brought by the industrial revolution, colonization, and globalization. 19

Towards a complexity theory of strategy

Abstract: Purpose – The purpose of this paper is to contribute to the creation of a complexity theory of strategy by integrating a number of ideas that have previously been explored independently in the strategy literature, namely improvisation, minimal structures, simple rules, dynamic capabilities, bricolage, and organizational resilience.Design/methodology/approach – Organizations are taken as complex adaptive systems that align with their environments through interaction and response rather than analysis and planning. The paper discusses how Schumpeterian environments influence organizations in the direction of simpler, minimally‐structured designs and considers why Schumpeterian environments create the need for strategic improvisation and minimally‐structured designs.Research limitations/implications – The paper articulates recent concepts in the management literature. The integration of these new concepts may be relevant to explore the way they relate with each other in the emerging organizational configurati...

Learning to live in a global commons: socioeconomic challenges for a sustainable environment

Abstract: Ecologists, economists and other social scientists have much incentive for interaction. First of all, ecological systems and socioeconomic systems are linked in their dynamics, and these linkages are key to coupling environmental protection and economic growth. Beyond this, however, are the obvious similarities in how ecological systems and socioeconomic systems function, and the common theoretical challenges in understanding their dynamics. This should not be surprising. Socioeconomic systems are in fact ecological systems, in which the familiar ecological phenomena of exploitation, cooperation and parasitism all can be identified as key features. Or, viewed from the opposite perspective, ecological systems are economic systems, in which competition for resources is key, and in which an evolutionary process shapes the individual agents to a distribution of specialization of function that leads to the emergence of flows and functionalities at higher levels of organization. Most fundamentally, ecological and socioeconomic systems alike are complex adaptive systems, in which patterns at the macroscopic level emerge from interactions and selection mechanisms mediated at many levels of organization, from individual agents to collectives to whole systems and even above. In such complex adaptive systems, robustness must be understood as emergent from selection processes operating at these many different levels, and the inherent nonlinearities can trigger sudden shifts in regimes that, in the case of the biosphere, can have major consequences for humanity. This lecture will explore the complex adaptive nature of ecosystems, and the implications for the robustness of ecosystem services on which we depend, and in particular examine the conditions under which cooperative behavior emerges. It will then turn attention to the socioeconomic systems in which environmental management is based, and ask what lessons can be learned from our examination of natural systems, and how we can modify social norms to achieve global cooperation in managing our common future. Of special interest will be issues of intragenerational and intergenerational equity, and the importance of various forms of discounting.

Innovation in organizations from a complex adaptive systems perspective

Abstract: A case for a balanced strategic approach to innovation is argued in the literature. March (1991) identified both short term exploitation and longer term exploration as essential but potentially conflicting organizational activities. Many organizations are good at incremental innovation but less successful at radical innovation which may partly explain a recent stress on the latter. Learning is key to successful innovation. In stable conditions, it tends to be a narrowing and converging process of testing. In chaotic conditions it is a process of expansion, divergence and discovery (Cheng and Van de Ven, 1996). The latter facilitates radical innovation, the former incremental innovation. Is a balance between them needed? Innovation ability is a key property of complex adaptive systems operating on ‘the edge of chaos’. This assists them survive over both long and short term futures. We consider how notions of organizations as complex adaptive systems can offer new insights into our understanding of learning and innovation.

Interpreting socio-technical co-evolution: applying complex adaptive systems to IS engagement

Abstract: Purpose – This paper seeks to understand how software systems and organisations co‐evolve in practice during an IS engagement. Seeks also to argue that complex adaptive system theory (CAS) provides an excellent lens to study the motor of co‐evolution due to its ability to frame the strategies and reinforcement models of actors and to illustrate this by recounting four narratives of the interaction, selection and adaptation of actors arising from a longitudinal case study of an IS engagement. Then sets out to consider how the complexity of the engagement emerges from the interrelationship of these narratives and how the adaptive behaviour of the various actors is both a response to and a driver of co‐evolution within the engagement.Design/methodology/approach – An interpretive case study was undertaken to examine the implementation of a novel academic scheduling and resource allocation system at a research‐intensive Australian university. The research was conducted over ten months, employing ethnographic m...

Chapter 30 Governing Social-Ecological Systems

Abstract: Social-ecological systems are complex adaptive systems where social and biophysical agents are interacting at multiple temporal and spatial scales. The main challenge for the study of governance of social-ecological systems is improving our understanding of the conditions under which cooperative solutions are sustained, how social actors can make robust decisions in the face of uncertainty and how the topology of interactions between social and biophysical actors affect governance. We review the contributions of agent-based modeling to these challenges for theoretical studies, studies which combines models with laboratory experiments and applications of practical case studies. Empirical studies from laboratory experiments and field work have challenged the predictions of the conventional model of the selfish rational agent for common pool resources and public-good games. Agent-based models have been used to test alternative models of decision-making which are more in line with the empirical record. Those models include bounded rationality, other regarding preferences and heterogeneity among the attributes of agents. Uncertainty and incomplete knowledge are directly related to the study of governance of social-ecological systems. Agent-based models have been developed to explore the consequences of incomplete knowledge and to identify adaptive responses that limited the undesirable consequences of uncertainties. Finally, the studies on the topology of agent interactions mainly focus on land use change, in which models of decision-making are combined with geographical information systems. Conventional approaches in environmental economics do not explicitly include non-convex dynamics of ecosystems, non-random interactions of agents, incomplete understanding, and empirically based models of behavior in collective action. Although agent-based modeling for social-ecological systems is in its infancy, it addresses the above features explicitly and is therefore potentially useful to address the current challenges in the study of governance of social-ecological systems.

Complexity, Networking, & Effects-Based Approaches to Operations

Abstract: : Our world is a myriad of ever-changing, interdependent variables whose courses we can never entirely predict. The strength of an effects-based approach to operations is that it squarely addresses these complexities by concentrating on their most nonlinear aspects: humans, their institutions, and their actions. Indeed, the entire effects-based approach can be characterized by four things: a focus on the human dimension of competition and conflict; the consideration of a full spectrum of actions whether in peace, crisis, or hostilities; a multifaceted, whole-of-nation concept of power; and the recognition of the complex interconnected nature of the actors and challenges involved. The human dimension arises because all effects-based approaches are ultimately about shaping human perceptions and behavior, and because they depend heavily on human beings to make the complex estimates and decisions involved. The focus on an entire spectrum of actions means thinking holistically across a peace-crisis-hostilities spectrum. Finally, any effects-based approach must proceed from the recognition that all actions and the reactions they provoke are inextricably linked in a system of ever-changing and adapting human systems whose complexity shapes both the nature of the problem and the task of assessing, planning, and executing any operation. The central tenet of an effects-based approach to operations is that we can somehow purposefully shape the interactions of the actors in this complex security environment. Living systems theory offers a way of approaching this complexity. It sees the world in biological and sociological terms as an interlocking multilevel system of complex adaptive systems from which no individual system can be extracted without changing both its character and that of the system as a whole. In the model, interactions occur simultaneously on many different levels with each interaction tending to proceed at a pace dictated by local circumstances.

Complexity Theory and Education

Abstract: This paper introduces central tenets of complexity theory and current issues that they raise, including: the consequences of unpredictability for knowing, responsibility, morality and planning; the significance of networking and connectedness; non-linear learning organizations; setting conditions for change by emergence and self-organization; fostering feedback for learning; changing external and internal environments; schools and learners as open, complex adaptive systems; cooperation and competition; pedagogy; and the significance of context. This paper acts as an introduction to the Special Interest Group and the other papers, teasing out several applications of complexity theory, including: online learning; staff development; the nature and facilitation of change; curriculum change and innovation; complexity theory and Bernstein's visible and invisible pedagogies; and the questioning of complexity theory's contribution to the moral debate over schooling. The paper introduces the context of Macau as an emergent, self-organizing territory, and locates several of the subsequent papers in this context, focusing on the fields of nursing education; premature school leaving; parental involvement in education; and curriculum change. Examples of online learning and school development from Hong Kong are also provided. The paper provides a theoretical and practical introduction to the field, with examples deliberately drawn from diverse aspects of education,

Australian rangelands as complex adaptive systems: A conceptual model and preliminary results

Abstract: Models to support decisions on rangeland policy must address the close links between ecological, economic, and social processes, and the adaptation of participants through time. We used an agent-based modeling approach to implement a parsimonious conceptual model of rangelands that included biophysical processes central to the functioning of rangelands, commercial enterprises, and institutions. The model operated on a monthly time step, and used economic and biophysical conditions to stimulate changes in management policies and learning. Our simple model reproduced the general patterns of forage growth and livestock dynamics in north-east Australia, and results illustrate consequences of interactions between environmental heterogeneity and learning rate.

Why is Economics not a Complex Systems Science

Abstract: Economics is viewed as a discipline that is mainly concerned with ‘simplistic’ theorizing, centered upon constrained optimization. As such, it is ahistorical and outcome focused, ie, it does not deal with economic processes. It is argued that all parts of the economy are inhabited by complex adaptive systems operating in complicated historical contexts and that this should be acknowledged at the core of economic analysis. It is explained how economics changes in fundamental ways when such a perspective is adopted, even if the presumption that people will try to optimize subject to constraints is retained. This is illustrated through discussion of how the production function construct has been used to provide an abstract representation of the network structures that exist in complex adaptive systems such as firms. It is argued that this has led to a serious understatement of the importance of rule systems that govern the connections in productive networks. The macroeconomics of John Maynard Keynes is then revisited to provide an example of how some economists in earlier times were able to provide powerful economic analysis that was based on intuitions that we can now classify as belonging to complex systems perspective on the economy. Throughout the paper, the reasons why a complex systems perspective did not develop in the mainstream of economics in the 20 th Century, despite the massive popularity of an economist like Keynes, are discussed and this is returned to in the concluding section where the prospect of paradigmatic change occurring in the future is evaluated.

An adaptive strategy for managing knowledge in organizations

Abstract: Purpose – This article proposes an adaptive strategy for managing knowledge in complex organizations. Specifically, this article aims to extend understanding in the field of knowledge management (KM) by examining how an adaptive strategy for managing knowledge can help organizations become innovative and build dynamic capabilities.Design/methodology/approach – Literature on complexity theory and KM is reviewed to propose the development of an adaptive strategy that will assist organization in managing knowledge and becoming innovative. The paper is structured around the following constructs: complexity theory, complex adaptive systems, and KM.Findings – A link between an adaptive strategy for managing knowledge, innovation and dynamic capability is established. The central proposition of the article is the organizations that follow adaptive complex processes for managing knowledge are better able to compete in the market today.Research limitations/implications – This article extends prior research on KM b...

Australian pastoralists in time and space: the evolution of a complex adaptive system

Abstract: Newcomers and exotic livestock have displaced indigenous hunter-gatherers from Australia's drylands over the past 200 yr. This paper seeks to learn from and explain the adaptive process involving the initially nave newcomers, their stock, and Australia's ancient landscapes. We review pastoral adaptation at the national, regional, and enterprise scales. These scales are linked, and so we use "panarchy" theory with its concept of "adaptive cycles" as an analytical framework. Past pastoral adaptation can be summarized by changes in key linkages: pastoralists (1) are now connected to more individuals than when they first moved into the rangelands, but are less reliant on local hubs for these connections; (2) have weaker links to the environment as environmental feedbacks have been reduced; (3) have stronger links to alternate land uses, but weaker links to governance; and (4) have stronger links to the global economy. Further change is inevitable. Pastoralism is likely to remain as the core activity in Australian rangelands, but the dynamic linkages that shape the system will, in future, connect pastoralists more strongly to post-production economies, information and more distant social networks, and to a more diverse group of land users.

Thinking in groups

Abstract: Is cognition an exclusive property of the individual or can groups have a mind of their own? We explore this question from the perspective of complex adaptive systems. One of the principal insights from this line of work is that rules that govern behavior at one level of analysis (the individual) can cause qualitatively different behavior at higher levels (the group). We review a number of behavioral studies from our lab that demonstrate how groups of people interacting in real-time can self-organize into adaptive, problem-solving group structures. A number of principles are derived concerning the critical features of such “distributed” information processing systems. We suggest that while cognitive science has traditionally focused on the individual, cognitive processes may manifest at many levels including the emergent group-level behavior that results from the interaction of multiple agents and their environment.

The evolution of an evolutionary perspective on B2B business

Abstract: Purpose – The paper seeks to review recent developments in theory and research regarding the nature and role of relations and networks in business markets and to argue for a more dynamic, interactive and evolutionary view.Design/methodology/approach – Complexity theory, as well as theories of distributed cognition and control, is used to show that business markets, relations and networks are complex adaptive systems of interacting people, firms, activities, resources and ideas in which no one player is in control.Findings – The theoretical perspective described has profound implications for management practice, policymaking and research. In particular it leads to the concept of soft assembled strategies in which management and firms utilize the inherent response properties of the relations and networks in which they operate to extend what they can do, sense, know and think.Research limitations/implications – Relevant research methodologies for addressing the academic, management and policy issues arising ...

The UK grocery business: towards a sustainable model for virtual markets

Abstract: Purpose – With the emergence of enabling internet technologies and increased competition between UK supermarkets has led the “big four” – Tesco, J Sainsbury, ASDA and Safeway/Morrisons – to develop grocery operations online. The objective of this paper is to evaluate and present best practice strategies employed by major retail organisations concerning these deployments. The paper argues that Tesco's superior performance can be identified through five critical factors. However, continued success using existing models and thinking is problematic and that future advantages will rely on taking a complex adaptive systems view of the deployment of E‐Grocery systems.Design/methodology/approach – The methodology employed is a conceptual synthesis of current knowledge, based on theoretical constructs and empirical observations.Findings – There is evidence of varying degrees of progress and lessons learnt, from adopting strategies and internet technologies, with new ways of conceptualizing and managing virtual ret...

Dispersed network manufacturing: adapting SMEs to compete on the global scale

Abstract: Purpose – To develop a conceptual framework for a new form of production system unique from many perspectives. The proposed system is based on the creation of a network of plants that are electronically linked so that the participating members focus on their specialized tasks yet also share their manufacturing and production resources to create a loosely structured and flexible enterprise.Design/methodology/approach – To introduce dispersed network manufacturing (DNM) as a new business model, and to discuss dispersed manufacturing network (DMN) as a possible realization of DNM. To link DMN to complex adaptive systems and to provide a prototype as to how SMEs can form a dynamic and adaptive network to create competitive advantages on both collaborative and individual scales.Findings – The notion of DNM advocates a reciprocal bonding among network members but calls for no obligatory egalitarian responsibility to one another. This research shows the feasibility of a network of plants that are electronically ...

A framework for improving health in cities: a discussion paper.

Abstract: This paper considers health in cities from the perspective of complex adaptive systems. This approach has a number of important implications for intervention that do not emerge in traditional accounts of cities and health. The paper reviews various accounts of the nature of cities and of health as well as the traditional urban health and Healthy Cities movements. It then provides a framework for intervention and tests it against an actual case study. It concludes that a complex adaptive systems framework opens up fresh possibilities for improving health in urban contexts.

Complexity: A Frontier for Management Education:

Abstract: This article critiques the mechanistic grounding of traditional management education and proposes complexity science as a fitting explanatory model for an age of complexity, contributing timely and important educational content and instructional processes to management education. It highlights some of those contributions and reviews instructional methods exemplifying key features of complex adaptive systems and suggesting the value in harnessing natural tendencies of systems by working in harmony with them. The article concludes with a consideration of issues facing teachers who contemplate teaching in accordance with the implications of complexity science.

A Play of Four Arenas How Complexity Can Serve Management Development

Abstract: Today’s rapidly changing business environment makes organizations pay special attention to the functioning of their internal processes. Among other things, the processes of management development (MD) are expected to reflect better the new competitive reality, which is characterized by dynamism, connectivity, non-linearity and emergent properties. This article studies MD in the light of complex adaptive systems (CAS), and presents key ideas of a systems approach to MD. The article elaborates a framework that combines MD’s situational context, developmental guidelines derived from the CAS theory, and examples of relevant MD practices. The framework offers MD professionals a practical means to assess and strengthen MD’s role in business. Furthermore, directions for future research on systems-based MD are brought up.