Complex adaptive system

About: Complex adaptive system is a research topic. Over the lifetime, 3190 publications have been published within this topic receiving 111947 citations. The topic is also known as: Complex adaptive system, CAS.

Robust Adaptive Strategies

Abstract: Strategy development requires that managers predict the future in an inherently uncertain world. Many mistakenly do so on the basis of perceived historical patterns that, according to recent scientific understanding of complex systems, do not have great predictive value. Complex systems consisting of many dynamically interacting parts are difficult and often impossible to predict because they exhibit punctuated equilibrium (periods of relative quiescence interspersed with episodes of dramatic change) and path dependence (small, random changes at one point in time that lead to radically different outcomes later). What, then, is a strategist to do? Beinhocker recommends cultivating and managing populations of multiple strategies that evolve over time, because the forces of evolution acting on a population of strategies make them more robust and adaptive. Because both biological evolution and business evolution are complex adaptive systems, to better understand business strategy, managers can employ a tool that scientists use to better understand biological evolution. An imaginary grid called a fitness landscape is an aid to comprehending how evolution increases the odds of survival in nature. In general, the rules for success in fitness landscapes also apply to business problems, though their specific application differs significantly by company and situation. The lessons of fitness landscapes offer an untraditional picture of what a company needs to develop a successful strategy. Because shifting an organization to this way of thinking about strategy is not easy, a company can take six actions to reinforce the robust, adaptive mind-set: ? Invest in a diversity of strategies. ? Evaluate strategies as real options that may open future possibilities, and remove biases that undervalue experimentation and flexibility. ? Diversify strategies along three dimensions ? time frame, risk, and relatedness to current business. ? Ensure that the strategies include sufficiently diverse initiatives in promising areas. ? Check that selection pressures on the firm's population of strategies reflect those operating on the population of strategies in the marketplace. ? Use venture capital performance metrics.

Managing health care organizations: where professionalism meets complexity science

Abstract: This article examines the intersection of professionalism and complexity science as a source of new insights for improving the health care industry from both a clinical and business point of view. Viewing health care organizations as professional complex adaptive systems suggests eight leadership tasks for addressing the circumstances that engulf health care. Managers who adopt this view will be able to create new levers for positive movement in their organizations.

Understanding Change in Primary Care Practice Using Complexity Theory

Abstract: Background Understanding the organization of primary care practices is essential for implementing changes related to delivery of preventive or other health care services A theoretical model derived from complexity theory provides a framework for understanding practice change Methods Data were reviewed from brief participant observation fieldnotes collected in the 84 practices of the Direct Observation of Primary Care (DOPC) study and in 27 practices from three similar studies investigating preventive services delivery These data were synthesized with information from an extensive search of the social science, nursing, and health services literature concerning practice organization, and of the literature on complexity theory from the fields of mathematics, physics, biology, management, medicine, and family systems, to create a complexity model of primary care practice Results Primary care practices are understood as complex adaptive systems consisting of agents, such as patients, office staff, and physicians, who enact internal models of income generation, patient care, and organizational operations These internal models interact dynamically to create each unique practice The particular shape of each practice is determined by its primary goals The model suggests three strategies for promoting change in practice and practitioner behavior: joining, transforming, and learning Conclusions This model has important implications for understanding change in primary care practice Practices are much more complex than present strategies for change assume The complexity model identified why some strategies work in particular practices and others do not

Information systems strategy: Past, present, future?

Abstract: The purpose of this paper is to contribute to the current discourse in the Strategic Information Systems (SIS) domain about the future and identity of SIS. We draw on Nelson's theorisation of the co-evolution of Physical and Social Technologies to redefine the SIS domain as a Complex Adaptive System (CAS) for the co-evolution of ICT and organisational capabilities and business models to create social and economic value. We conduct a meta-analysis of the domain based on a longitudinal review of SIS research over 33years, and contrary to contemporaneous SIS literature which suggests that a paradigm shift may be necessary to address the increased turbulence, uncertainty and dynamism in the emerging competitive landscape, we find that the SIS research domain has the requisite adaptive capacity to evolve gracefully to address the challenges of the emerging networked competitive landscape. Drawing on complexity science and network theory we identify four priorities for the development of the domain for the future: conceptualisation of the SIS Domain as a CAS for the co-evolution of Physical and Social Technologies; the adoption of the network paradigm; access to a science of networks; and adoption of Complexity Science as an articulation device within SIS and across disciplines.