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Articles de revues sur le sujet « Complex and adaptive system »

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Auteur : Grafiati
Publié le 14 mars 2023

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1

Oughton, Edward J., Will Usher, Peter Tyler et Jim W. Hall. « Infrastructure as a Complex Adaptive System ». Complexity 2018 (4 novembre 2018) : 1–11. http://dx.doi.org/10.1155/2018/3427826.

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National infrastructure systems spanning energy, transport, digital, waste, and water are well recognised as complex and interdependent. While some policy makers have been keen to adopt the narrative of complexity, the application of complexity-based methods in public policy decision-making has been restricted by the lack of innovation in associated methodologies and tools. In this paper we firstly evaluate the application of complex adaptive systems theory to infrastructure systems, comparing and contrasting this approach with traditional systems theory. We secondly identify five key theoretical properties of complex adaptive systems including adaptive agents, diverse agents, dynamics, irreversibility, and emergence, which are exhibited across three hierarchical levels ranging from agents, to networks, to systems. With these properties in mind, we then present a case study on the development of a system-of-systems modelling approach based on complex adaptive systems theory capable of modelling an emergent national infrastructure system, driven by agent-level decisions with explicitly modelled interdependencies between energy, transport, digital, waste, and water. Indeed, the novel contribution of the paper is the articulation of the case study describing a decade of research which applies complex adaptive systems properties to the development of a national infrastructure system-of-systems model. This approach has been used by the UK National Infrastructure Commission to produce a National Infrastructure Assessment which is capable of coordinating infrastructure policy across a historically fragmented governance landscape spanning eight government departments. The application will continue to be pertinent moving forward due to the continuing complexity of interdependent infrastructure systems, particularly the challenges of increased electrification and the proliferation of the Internet of Things.
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Smith, Richard M., et Mark A. Bedau. « Is Echo a Complex Adaptive System ? » Evolutionary Computation 8, no 4 (décembre 2000) : 419–42. http://dx.doi.org/10.1162/106365600568248.

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We evaluate whether John Holland's Echo model exemplifies his theory of complex adaptive systems. After reviewing Holland's theory of complex adaptive systems and describing his Echo model, we describe and explain the characteristic evolutionary behavior observed in a series of Echo model runs. We conclude that Echo lacks the diversity of hierarchically organized aggregates that typify complex adaptive systems, and we explore possible explanations for this failure.
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Matos, Francisco Gomes de. « Language as a complex adaptive system ». DELTA : Documentação de Estudos em Lingüística Teórica e Aplicada 26, no 2 (2010) : 425–28. http://dx.doi.org/10.1590/s0102-44502010000200010.

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Alberto, Díaz, Castilla Alberto et Lebersztein Gabriel. « The Hospital : A Complex Adaptive System ». Asian Journal of Medicine and Health 5, no 1 (10 janvier 2017) : 1–5. http://dx.doi.org/10.9734/ajmah/2017/34421.

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Lierman, Steven. « Law as a Complex Adaptive System ». Maastricht Journal of European and Comparative Law 21, no 4 (décembre 2014) : 611–29. http://dx.doi.org/10.1177/1023263x1402100403.

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Bobo, Lawrence D. « RACE AS A COMPLEX ADAPTIVE SYSTEM ». Du Bois Review : Social Science Research on Race 15, no 02 (2018) : 211–15. http://dx.doi.org/10.1017/s1742058x19000043.

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Armstrong, Gordon. « Theatre as a Complex Adaptive System ». New Theatre Quarterly 13, no 51 (août 1997) : 277–88. http://dx.doi.org/10.1017/s0266464x00011271.

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The functioning of human consciousness in interpreting and staging a theatrical performance is, as Gordon Armstrong argues in this article, among the most highly selective and adaptive operations known to physical science. According to this view, the theatre, as a substrate of consciousness, was part of the package that defined modern man as a reflective species: whereas for the first four million years of human existence man was silent about a probable inner life, the dawn of empathy some 200,000 years ago saw a neural explosion – the enlargement of the angular gyrus in the left hemisphere of the brain, unlocking a new kind of reflective consciousness. In isolation, this aberrant neurological connection proved so advantageous for hunting and for communication that members of a tribe who possessed this aberration prospered: and adaptation to the ice ages that began 200,000 years ago was a motivating factor in stimulating the emergence of what we can recognize as art. Gordon Armstrong is immediate past Secretary of the American Society for Theatre Research, and Review Editor for Theatre Research International. He has taught at UCLA, SUNY Stony Brook, and the University of Rhode Island, and has designed and directed productions in San Francisco, Los Angeles, and New York. His full-length works include the revised Golden Ages of the Theatre and Samuel Beckett, W.B. Yeats, and Jack Yeats: Images and Words.
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Schwab, E. D., et K. J. Pienta. « Cancer as a complex adaptive system ». Medical Hypotheses 47, no 3 (septembre 1996) : 235–41. http://dx.doi.org/10.1016/s0306-9877(96)90086-9.

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Haris, Khaled, et Cihan H. Dagli. « Adaptive Reconfiguration of Complex System Architecture ». Procedia Computer Science 6 (2011) : 147–52. http://dx.doi.org/10.1016/j.procs.2011.08.029.

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Lenton, Timothy M., et Marcel van Oijen. « Gaia as a complex adaptive system ». Philosophical Transactions of the Royal Society of London. Series B : Biological Sciences 357, no 1421 (29 mai 2002) : 683–95. http://dx.doi.org/10.1098/rstb.2001.1014.

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We define the Gaia system of life and its environment on Earth, review the status of the Gaia theory, introduce potentially relevant concepts from complexity theory, then try to apply them to Gaia. We consider whether Gaia is a complex adaptive system (CAS) in terms of its behaviour and suggest that the system is self–organizing but does not reside in a critical state. Gaia has supported abundant life for most of the last 3.8 Gyr. Large perturbations have occasionally suppressed life but the system has always recovered without losing the capacity for large–scale free energy capture and recycling of essential elements. To illustrate how complexity theory can help us understand the emergence of planetary–scale order, we present a simple cellular automata (CA) model of the imaginary planet Daisyworld. This exhibits emergent self–regulation as a consequence of feedback coupling between life and its environment. Local spatial interaction, which was absent from the original model, can destabilize the system by generating bifurcation regimes. Variation and natural selection tend to remove this instability. With mutation in the model system, it exhibits self–organizing adaptive behaviour in its response to forcing. We close by suggesting how artificial life (‘Alife’) techniques may enable more comprehensive feasibility tests of Gaia.
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Kepeng, Feng, et Tian Juncang. « Complex Adaptive System on Water Resources Allocation System ». Journal of Applied Sciences 13, no 9 (15 avril 2013) : 1530–36. http://dx.doi.org/10.3923/jas.2013.1530.1536.

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Wei, Qiang, Xing-yuan Wang et Xiao-peng Hu. « Adaptive hybrid complex projective synchronization of chaotic complex system ». Transactions of the Institute of Measurement and Control 36, no 8 (19 mai 2014) : 1093–97. http://dx.doi.org/10.1177/0142331214534722.

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John, Thomas, et Mantri Pam. « Complex Adaptive Blockchain Governance ». MATEC Web of Conferences 223 (2018) : 01010. http://dx.doi.org/10.1051/matecconf/201822301010.

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The blockchain revolution upholds the decentralizing ideal of “control nothing.” It is natural that such a pursuit would face issues of governance that demand reasonable control; control that is both operational as well as adaptive in nature. Eliminating middlemen and handing over controls to a trusted system of trustless agents does not thereby bestow trust across time. This is especially true when relentless change is the order of the day. Issues of governance rise up when blockchain systems (especially those that have embedded smart contracts) are forced to operate increasingly away from their original intent. Smart contracts need governance when beset with the problem of the unknown-unknowns. Guided by the axiomatic approach, this paper looks at the paradoxical issue of blockchain governance from a Complex Adaptive Systems (CAS) perspective that helps frame the fundamental problem of decentralization. The objective is to solve the Blockchain Governance Kernel Design. Real-life examples are used to illustrate the findings.
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Khayut, Ben, Lina Fabri et Maya Avikhana. « Modeling of Intelligent System Thinking in Complex Adaptive Systems ». Procedia Computer Science 36 (2014) : 93–100. http://dx.doi.org/10.1016/j.procs.2014.09.043.

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Sturmberg, Joachim P., Di M. O'Halloran et Carmel M. Martin. « Understanding health system reform - a complex adaptive systems perspective ». Journal of Evaluation in Clinical Practice 18, no 1 (5 janvier 2012) : 202–8. http://dx.doi.org/10.1111/j.1365-2753.2011.01792.x.

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Lansing, J. Stephen. « Complex Adaptive Systems ». Annual Review of Anthropology 32, no 1 (octobre 2003) : 183–204. http://dx.doi.org/10.1146/annurev.anthro.32.061002.093440.

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Minas, Harry. « Leadership for Change in Complex Systems ». Australasian Psychiatry 13, no 1 (mars 2005) : 33–39. http://dx.doi.org/10.1080/j.1440-1665.2004.02147.x.

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Objectives: To examine clinician leadership for change from the perspective of complexity. Methods: The core features of complex adaptive systems are described and examples of these characteristics are identified in Australia's mental health system. The implications of conceiving of themental health system as a complex adaptive system are explored. Conclusions: It is concluded that there is value in conceiving of Australia's mental health system as a complex adaptive system and that such a conception provides useful guidance for leadership for change and for management.
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Kaidonis, J. A., S. Ranjitkar, G. C. Townsend, K. S. B. Koh, V. K. L. Toh et A. H. Brook. « The mature stomatognathic system is a complex adaptive system ». International Journal of Design & ; Nature and Ecodynamics 11, no 4 (1 octobre 2016) : 670–75. http://dx.doi.org/10.2495/dne-v11-n4-670-675.

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Rzevski, George, Sergei Kozhevnikov et Miroslav Svitek. « Smart City as a Complex Adaptive System ». Ontology of designing 10, no 1 (6 avril 2020) : 7–21. http://dx.doi.org/10.18287/2223-9537-2020-10-1-7-21.

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CROFT, WILLIAM. « STUDYING LANGUAGE AS A COMPLEX ADAPTIVE SYSTEM ». ENGLISH LINGUISTICS 31, no 1 (2014) : 1–21. http://dx.doi.org/10.9793/elsj.31.1_1.

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Janssen, M. A., et W. J. M. Martens. « Modeling Malaria as a Complex Adaptive System ». Artificial Life 3, no 3 (juillet 1997) : 213–36. http://dx.doi.org/10.1162/artl.1997.3.3.213.

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As the resistance of the malaria parasite to antimalarial drugs continues to increase, as does that of the malarial mosquito to insecticides, the efficacy of efforts to control malaria in many tropical countries is diminishing. This trend, together with the projected consequences of climate change, may prove to exacerbate substantially the significance of malaria in the coming decades. In this article we introduce the use of an evolutionary modeling approach to simulate the adaptation of mosquitoes and parasites to the available pesticides and drugs. By coupling genetic algorithms with a dynamic malaria-epidemiological model, we derive a complex adaptive system capable of simulating adapting and evolving processes within both the mosquito and the parasite populations. This approach is used to analyze malaria management strategies appropriate to regions of higher and lower degrees of endemicity. The results suggest that adequate use of insecticides and drugs may reduce the occurrence of malaria in regions of low endemicity, although increased efforts would be necessary in the event of a climate change. However, our model indicates that in regions of high endemicity the use of insecticides and drugs may lead to an increase in incidence due to enhanced resistance development. Projected climate change, on the other hand, may lead to a limited reduction of the occurrence of malaria due to the presence of a higher percentage of immune persons in the older age class.
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Ibrahim, Yosif A. « Managing Stormwater as a Complex Adaptive System ». Journal of Hydrologic Engineering 24, no 10 (octobre 2019) : 04019040. http://dx.doi.org/10.1061/(asce)he.1943-5584.0001837.

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Pacheco, Jorge M., Vítor V. Vasconcelos et Francisco C. Santos. « Climate governance as a complex adaptive system ». Physics of Life Reviews 11, no 4 (décembre 2014) : 595–97. http://dx.doi.org/10.1016/j.plrev.2014.10.003.

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Shanker, Murali, Marina N. Astakhova et Cathy L. Z. DuBois. « Sexual Harassment : A Complex Adaptive System Viewpoint ». Gender, Technology and Development 19, no 3 (janvier 2015) : 239–70. http://dx.doi.org/10.1177/0971852415596861.

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Zhao, L., G. Yang, W. Wang, Y. Chen, J. P. Huang, H. Ohashi et H. E. Stanley. « Herd behavior in a complex adaptive system ». Proceedings of the National Academy of Sciences 108, no 37 (29 août 2011) : 15058–63. http://dx.doi.org/10.1073/pnas.1105239108.

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Muffatto, Moreno, et Matteo Faldani. « Open Source as a Complex Adaptive System ». Emergence 5, no 3 (septembre 2003) : 83–100. http://dx.doi.org/10.1207/s15327000em0503_8.

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Ellis, Paul. « Hong Kong as a complex adaptive system ». Asia Pacific Business Review 6, no 1 (octobre 1999) : 33–55. http://dx.doi.org/10.1080/13602380012331289100.

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Wollin, Drew, et Chad Perry. « Marketing management in a complex adaptive system ». European Journal of Marketing 38, no 5/6 (mai 2004) : 556–72. http://dx.doi.org/10.1108/03090560410529213.

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Taylor, Charles E., et Martin L. Cody. « Bird song : a model complex adaptive system ». Artificial Life and Robotics 20, no 4 (7 novembre 2015) : 285–90. http://dx.doi.org/10.1007/s10015-015-0231-z.

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UNOLD, OLGIERD. « SELF-ADAPTIVE LEARNING CLASSIFIER SYSTEM ». Journal of Circuits, Systems and Computers 19, no 01 (février 2010) : 275–96. http://dx.doi.org/10.1142/s0218126610006256.

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This article introduces a new kind of self-adaptation in discovery mechanism of learning classifier system XCS. Unlike the previous approaches, which incorporate self-adaptive parameters in the representation of an individual, proposed model evolves competitive population of the reduced XCSs, which are able to adapt both classifiers and genetic parameters. The experimental comparisons of self-adaptive mutation rate XCS and standard XCS interacting with 11-bit, 20-bit, and 37-bit multiplexer environment were provided. It has been shown that adapting the mutation rate can give an equivalent or better performance to known good fixed parameter settings, especially for computationally complex tasks. Moreover, the self-adaptive XCS is able to solve the problem of inappropriate for a standard XCS parameters.
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Akgün, Ali E., Halit Keskin, John C. Byrne et Özgün Ö. Ilhan. « Complex adaptive system mechanisms, adaptive management practices, and firm product innovativeness ». R&D Management 44, no 1 (25 décembre 2013) : 18–41. http://dx.doi.org/10.1111/radm.12036.

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Zhang, Ruoxun, Yongli Liu et Shiping Yang. « Adaptive Synchronization of Fractional-Order Complex Chaotic system with Unknown Complex Parameters ». Entropy 21, no 2 (21 février 2019) : 207. http://dx.doi.org/10.3390/e21020207.

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This paper investigates the problem of synchronization of fractional-order complex-variable chaotic systems (FOCCS) with unknown complex parameters. Based on the complex-variable inequality and stability theory for fractional-order complex-valued system, a new scheme is presented for adaptive synchronization of FOCCS with unknown complex parameters. The proposed scheme not only provides a new method to analyze fractional-order complex-valued system but also significantly reduces the complexity of computation and analysis. Theoretical proof and simulation results substantiate the effectiveness of the presented synchronization scheme.
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Holland, John H. « Studying Complex Adaptive Systems ». Journal of Systems Science and Complexity 19, no 1 (mars 2006) : 1–8. http://dx.doi.org/10.1007/s11424-006-0001-z.

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Cao, Hai Wang, et Chao Gai Xue. « Self-Organization System Framework of Enterprise Information System Based on CAS ». Advanced Materials Research 591-593 (novembre 2012) : 2628–31. http://dx.doi.org/10.4028/www.scientific.net/amr.591-593.2628.

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In order to avoid enterprise information system (EIS) risk, the self-organization mechanism of EIS based on complex adaptive system (CAS) is studied. Firstly, self-organization properties of EIS are analyzed, which include open system, nonlinear characteristics, far from equilibrium and fluctuations. Secondly, the complex properties and complex adaptive properties of EIS self-organization are studied. The complex properties include multi-agent, active adaptation of agents, multi-level nature, technology complexity, organizational complexity, process complexity and environment complexity. The complex adaptive properties include aggregation mechanism, identification mechanism, non-linear characteristics flow characteristics, diversity characteristics, internal model mechanism and block characteristics. Finally, architecture model of EIS self-organization is proposed as well as its macro and micro models, which provides a new perspective for EIS and helps understand the rules of EIS implementation.
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Karwowski, Waldemar. « A Review of Human Factors Challenges of Complex Adaptive Systems ». Human Factors : The Journal of the Human Factors and Ergonomics Society 54, no 6 (décembre 2012) : 983–95. http://dx.doi.org/10.1177/0018720812467459.

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Objective: In this paper, the author explores a need for a greater understanding of the true nature of human–system interactions from the perspective of the theory of complex adaptive systems, including the essence of complexity, emergent properties of system behavior, nonlinear systems dynamics, and deterministic chaos. Background: Human performance, more often than not, constitutes complex adaptive phenomena with emergent properties that exhibit nonlinear dynamical (chaotic) behaviors. Methods: The complexity challenges in the design and management of contemporary work systems, including service systems, are explored. Examples of selected applications of the concepts of nonlinear dynamics to the study of human physical performance are provided. Results: Understanding and applications of the concepts of theory of complex adaptive and dynamical systems should significantly improve the effectiveness of human-centered design efforts of a large system of systems. Conclusion: Performance of many contemporary work systems and environments may be sensitive to the initial conditions and may exhibit dynamic nonlinear properties and chaotic system behaviors. Human-centered design of emergent human–system interactions requires application of the theories of nonlinear dynamics and complex adaptive system. Application: The success of future human–systems integration efforts requires the fusion of paradigms, knowledge, design principles, and methodologies of human factors and ergonomics with those of the science of complex adaptive systems as well as modern systems engineering.
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지명구. « The Complex Adaptive System of the Animation Padak ». Journal of Korea Design Forum ll, no 44 (août 2014) : 305–14. http://dx.doi.org/10.21326/ksdt.2014..44.026.

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Morse, Wayde C. « Recreation as a Social-Ecological Complex Adaptive System ». Sustainability 12, no 3 (21 janvier 2020) : 753. http://dx.doi.org/10.3390/su12030753.

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The environment and society are both the context for and product of human actions and interactions. Outdoor recreation is the primary interaction many people have with the environment and it is an interaction that greatly contributes to human well-being. To sustainably manage the social and ecological components of outdoor recreation, an integrative and dynamic systems perspective is needed. Analyses that link recreation management and recreational experiences to both social and ecological outcomes across multiple sales and over time are not developed. This article will outline how a number of fragmented recreation management frameworks such as the recreation experience model, beneficial outcomes, the recreation opportunity spectrum, limits of acceptable change, and constraints theory can be organized within a larger social-ecological framework. The outdoor recreation meta-framework presented here links structuration theory from the social sciences with theories of complex adaptive systems and hierarchical patch dynamics from ecology to understand the human and ecological drivers for and responses to outdoor recreation.
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Rooney, Jim, et Yiyuan Cao. « Outsourced supply chains as a complex adaptive system ». Meditari Accountancy Research 27, no 2 (8 avril 2019) : 170–95. http://dx.doi.org/10.1108/medar-02-2018-0296.

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PurposeFirms in the early stage of their organisational lifecycle (ESFs) are subject to concerns founded on a requirement for strategic flexibility, prompting engagement in inter-organisational relationships such as outsourcing. However, studies of the management control dynamics of these relationships are rare. This paper aims to respond by empirically examining the influence of ESF managers on the ongoing management control of such relationships.Design/methodology/approachA single outsourcing case study is utilised to provide evidence in examining a multi-theoretical framework that adopts a complex adaptive system (CAS) perspective as a qualitative analytical framework, along with the existing accounting theory on control adoption.FindingsFocused on management concerns with tensions between inter-organisational control and strategic flexibility, this paper identifies reasons for the adoption of management controls by an ESF. The inter-organisational system explored in this paper emphasises the importance of adopting a holistic epistemology in understanding changes in control adoption.Research limitations/implicationsThis paper extends current theoretical perspectives on control adoption to consider the inter-organisational control concerns of ESF managers.Practical implicationsThe insights identified in this paper provide a systemic framework to identify potential organisational and environmental influences on control problems, emphasising environmental co-evolution rather than achievement of ideal equilibrium states.Originality/valueThe intended contribution is to extend the management control literature to consider the effect of organisational lifecycle on the adoption of new inter-organisational management controls in the wake of ongoing trade-off between competing inter-organisational requirements.
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Matthews, Jean I., et Paul T. Thomas. « Managing clinical failure : a complex adaptive system perspective ». International Journal of Health Care Quality Assurance 20, no 3 (8 mai 2007) : 184–94. http://dx.doi.org/10.1108/09526860710743336.

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Beckner, Clay, Richard Blythe, Joan Bybee, Morten H. Christiansen, William Croft, Nick C. Ellis, John Holland, Jinyun Ke, Diane Larsen-Freeman et Tom Schoenemann. « Language Is a Complex Adaptive System : Position Paper ». Language Learning 59 (décembre 2009) : 1–26. http://dx.doi.org/10.1111/j.1467-9922.2009.00533.x.

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Wellbrink, Joerg, Mike Zyda et John Hiles. « Modeling Vigilance Performance as a Complex Adaptive System ». Journal of Defense Modeling and Simulation : Applications, Methodology, Technology 1, no 1 (avril 2004) : 29–42. http://dx.doi.org/10.1177/154851290400100103.

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Basile, Gianpaolo, Giancarlo Scozzese et Maria Antonella Ferri. « Marketing and management : a complex adaptive system view ». World Review of Entrepreneurship, Management and Sustainable Development 12, no 2/3 (2016) : 134. http://dx.doi.org/10.1504/wremsd.2016.074976.

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Kurakin, Alexei, Andrzej Swistowski, Susan C. Wu et Dale E. Bredesen. « The PDZ Domain as a Complex Adaptive System ». PLoS ONE 2, no 9 (26 septembre 2007) : e953. http://dx.doi.org/10.1371/journal.pone.0000953.

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Kohno, Michimune, Masahiro Matsunaga et Yuichiro Anzai. « An adaptive sensor network system for complex environments ». Robotics and Autonomous Systems 28, no 2-3 (août 1999) : 115–25. http://dx.doi.org/10.1016/s0921-8890(99)00010-x.

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Liu, Haitao. « Language as a human-driven complex adaptive system ». Physics of Life Reviews 26-27 (novembre 2018) : 149–51. http://dx.doi.org/10.1016/j.plrev.2018.06.006.

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Yazdanbakhsh, Omolbanin, et Scott Dick. « FANCFIS : Fast adaptive neuro-complex fuzzy inference system ». International Journal of Approximate Reasoning 105 (février 2019) : 417–30. http://dx.doi.org/10.1016/j.ijar.2018.10.018.

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Tilchin, Oleg, et Mohammad Essawi. « A Collaborative Work System for Complex Adaptive Leadership ». International Journal of Knowledge, Culture, and Change Management : Annual Review 11, no 2 (2012) : 45–58. http://dx.doi.org/10.18848/1447-9524/cgp/v11i02/50107.

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Song, Kunyu, Kenan An, Guang Yang et Jiping Huang. « Risk-Return Relationship in a Complex Adaptive System ». PLoS ONE 7, no 3 (30 mars 2012) : e33588. http://dx.doi.org/10.1371/journal.pone.0033588.

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Stephens, Rick, et Michael Richey. « Accelerating STEM Capacity : A Complex Adaptive System Perspective ». Journal of Engineering Education 100, no 3 (juillet 2011) : 417–23. http://dx.doi.org/10.1002/j.2168-9830.2011.tb00020.x.

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Kim, Rakhyun E., et Brendan Mackey. « International environmental law as a complex adaptive system ». International Environmental Agreements : Politics, Law and Economics 14, no 1 (22 septembre 2013) : 5–24. http://dx.doi.org/10.1007/s10784-013-9225-2.

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