Complex Adaptive Socio-technical Systems Research Articles

Creating Agent-Based Energy Transition Management Models That Can Uncover Profitable Pathways to Climate Change Mitigation

The energy domain is still dominated by equilibrium models that underestimate both the dangers and opportunities related to climate change. In reality, climate and energy systems contain tipping points, feedback loops, and exponential developments. This paper describes how to create realistic energy transition management models: quantitative models that can discover profitable pathways from fossil fuels to renewable energy. We review the literature regarding agent-based economics, disruptive innovation, and transition management and determine the following requirements. Actors must be detailed, heterogeneous, interacting, learning, and strategizing. Technology should be represented as a detailed and heterogeneous portfolio that can develop in a bottom-up manner, using endogenous feedback loops. Assumptions about discount rates and the social cost of carbon should be configurable. The model should contain interactions between the global, national, local, and individual level. A review of modelling techniques shows that equilibrium models are unsuitable and that system dynamics and discrete event simulation are too limited. The agent-based approach is found to be uniquely suited for the complex adaptive sociotechnical systems that must be modelled. But the choice for agent-based models does not mean a rejection of other approaches because they can be accommodated within the agent-based framework. We conclude with practical guidelines.

IE = Industrial Evolution?

Background IE as a field studies systems that consist of a myriad of interconnected environmental, social, economic and technical systems. People, machines, organization, the bio-geo-chemical environment, infrastructures, markets, laws and habits form a complex adaptive socio-technical system, evolving through constant parallel and distributed interaction of heterogeneous social and technical elements. Understanding and shaping this evolution is essential if we are to rise to the challenges of climate change, resource scarcity, population growth and world peace. These system can be characterized as Complex Adaptive Systems, which John H. Holland [8] defines as:

Advancing the science of measurement of diagnostic errors in healthcare: the Safer Dx framework

Diagnostic errors are major contributors to harmful patient outcomes, yet they remain a relatively understudied and unmeasured area of patient safety. Although they are estimated to affect about 12 million...

Complex Adaptive Socio-Technical Systems The Role of Socio-Technical Networks in New Product Development

New product development (NPD) is challenging, as it involves mastering new technologies by coordinating appropriate resources efficiently and effectively. Established models of NPD focus on structuring, planning and ordering the innovation process but do not account for complexity and organizational responses and strategies in handling day-to-day resource allocation and decision-making. Our work is theoretically based on ideas from complexity science and NPD procedures. We build on and extend the work on Complex Adaptive System (CAS) and combine it with Socio-Technical System in an innovative approach to analyze, understand and manage NPD complexity by means of network analysis and performance metrics.This paper contributes to existing literature by introducing a framework of complex adaptive socio-technical systems (CASS). It is intended to (1) consider dependencies between product and individuals, (2) provide indicators to measure complexity, efficiency and effectiveness, (3) explain complex phenomena by identifying patterns, and (4) enable NPD governance.We demonstrate the applicability of our framework and metrics using comparative longitudinal case studies using novel and unique data from 4 years of meeting minutes and document exchange in the design phase of the NPD process of a large German automobile OEM. Results reveal new measures for addressing operational, social and technical complexity, providing new insights into complex dynamic behavior. From a managerial point of view, contributions of CASS are twofold: First, new possibilities for NPD governance emerge from performance indicators. Second, the extraction of dynamic socio-technical networks supports project-to-project learning.

ENTERPRISE ARCHITECTURE: ENABLING INTEGRATION, AGILITY AND CHANGE

Three core imperatives are essential for modern businesses and organizations: seamless integration of customer and operational processes, agility, and the ability to change. These imperatives are relevant in view of successfully executing strategic choices, but all too often not satisfied. Businesses and organizations are complex adaptive socio-technical systems and can be viewed from two fundamentally different perspectives: the functional (black-box) perspective and the constructional (white-box) perspective. Management and governance of businesses and organizations regard the functional, black-box perspective, which is inherently ill-suited for addressing the imperatives mentioned. It will be argued that establishing system integration, agility and change requires a focus on the system's design, hence necessitates the constructional perspective. The concept of architecture is considered fundamental for operationalizing the constructional perspective. Next to the more familiar notion of technology architecture, the concepts of business, organizational and information architecture are formally introduced and elucidated. Various domains within these architectures will be highlighted, whereby the importance of coherence and consistency is stressed, especially in view of the ability to change. Collectively, the four architectures are labeled Enterprise Architecture. Finally, enterprise architecture will be positioned as a crucial means for linking strategy development and execution.

Quantitation of Meissner's corpuscles in hereditary neurologic disorders. Charcot-Marie-Tooth disease, Roussy-Levy syndrome, Dejerine-Sottas disease, hereditary sensory neuropathy, spinocerebellar degenerations, and hereditary spastic paraplegia.

Diagnostic errors are major contributors to harmful patient outcomes, yet they remain a relatively understudied and unmeasured area of patient safety. Although they are estimated to affect about 12 million Americans each year in ambulatory care settings alone, both the conceptual and pragmatic scientific foundation for their measurement is under-developed. Health care organizations do not have the tools and strategies to measure diagnostic safety and most have not integrated diagnostic error into their existing patient safety programs. Further progress toward reducing diagnostic errors will hinge on our ability to overcome measurement-related challenges. In order to lay a robust groundwork for measurement and monitoring techniques to ensure diagnostic safety, we recently developed a multifaceted framework to advance the science of measuring diagnostic errors (The Safer Dx framework). In this paper, we describe how the framework serves as a conceptual foundation for system-wide safety measurement, monitoring and improvement of diagnostic error. The framework accounts for the complex adaptive sociotechnical system in which diagnosis takes place (the structure), the distributed process dimensions in which diagnoses evolve beyond the doctor9s visit (the process) and the outcomes of a correct and timely “safe diagnosis” as well as patient and health care outcomes (the outcomes). We posit that the Safer Dx framework can be used by a variety of stakeholders including researchers, clinicians, health care organizations and policymakers, to stimulate both retrospective and more proactive measurement of diagnostic errors. The feedback and learning that would result will help develop subsequent interventions that lead to safer diagnosis, improved value of health care delivery and improved patient outcomes.