Patrick T. Hester

Systems Theory as the Foundation for Understanding Systems

As currently used, systems theory is lacking a universally agreed upon definition. The purpose of this paper is to offer a resolution by articulating a formal definition of systems theory. This definition is presented as a unified group of specific propositions which are brought together by way of an axiom set to form a system construct: systems theory. This construct affords systems practitioners and theoreticians with a prescriptive set of axioms by which a system must operate; conversely, any set of entities identified as a system may be characterized by this set of axioms. Given its multidisciplinary theoretical foundation and discipline-agnostic framework, systems theory, as it is presented here, is posited as a general approach to understanding system behavior.

Interdependency-induced risk with applications to healthcare

Abstract Developing effective protection, mitigation and recovery measures for critical infrastructures is paramount in the wake of increasing natural and human-initiated hazards, risks and threats. Influencing these measures are interconnections (i.e., interdependencies) among infrastructure systems. Understanding the nature of system interdependencies can play an essential role in minimizing and/or reducing the probabilities and consequences of cascading failures in interdependent systems. This paper discusses the need for policy-makers, infrastructure operators and researchers to consider alternative approaches to formulating risk and enabling solutions to challenging 21st century issues related to interdependent infrastructures. Using the healthcare sector as an example, this paper suggests that identifying the risks associated with maintaining public health goes beyond traditional risk formulation to include the structural complexity brought about by infrastructure interdependencies.

Towards a theory of multi-method m&s approach: part III

This paper is the first from a series of papers that aim to develop a theory of multi-method M&S approach. The aim of this paper is to develop ontological basis for multi-method M&S approach. The first part of this paper discusses terms related to the use of more than a single modeling & simulation (M&S) method. This is to show the ontological ambiguity currently present within the M&S field in the context of using more than a single method. Next section provides the philosophical stance of the authors about the main terms in order to provide clarification and context of the term multi-method M&S approach. The last section takes these previous concepts and proposes a set of definitions relevant to a multi-method M&S approach, including its parent and derivative terms.

Exploration of purpose for multi-method simulation in the context of social phenomena representation

Difficulty of social phenomena representation can be related to limitations of used modeling techniques. More flexibility and creativity to represent social phenomena (an adequate mix of model scope, resolution, and fidelity) is desirable. The representation of social phenomena with a combination of different methods seems intuitively appealing, but the usefulness of this approach is questionable. Current view on the justification of multi-method has limitations in social science context, because it lacks a human dimension. This paper explores the literature that pertains to mixing methods, and displays current reasoning behind the use of the multi-method approach. The perspective on mixing methods from empirical social science projected onto M&S domain exposes high-level purposes related to representation of social phenomena with mixed method approaches. Based on the reviewed literature and qualitative analysis, the general view of ingredients for inferring purposefulness of the multi-method approach in the context of social phenomena representation is proposed.

Applying methods of the M&S spectrum for complex systems engineering

Systems engineering for complex systems or system of systems cannot rely on a single method for modeling and analysis. However, established methods ranging from system dynamics (SD) to agent based simulation (ABS) can be applied to analyze specific domains. This paper introduces a spectrum of modeling & simulation (M&S) methods ranging from differential equations and highly aggregated models to high resolution models of individual behavior. Orchestration and choreography of all methods in this spectrum allow the seamless and continuous evaluation of complex systems and system of systems. A proposed classification is illustrated through two example problem domains: traffic and evacuation modeling.

Stakeholders in systems problems

Stakeholders exist at the centre of all systems problems and are the principal contributors to the solution of these problems. We provide an approach for classifying stakeholders and determining an appropriate level of action to take with respect to these stakeholders that combines the power, legitimacy and urgency typology with a stakeholder attitude classification schema. The newly developed stakeholder strategy is a matrix that combines stakeholder attitude and classification. This matrix serves as a guide for the application of resources in support of stakeholder involvement. This technique provides systems practitioners with a means to deal with stakeholders effectively.

Examining metrics and methods for determining critical facility system effectiveness

Approaches for quantifying security system performance vary for different critical facilities, ranging from in-depth quantitative analyses to heuristics-based rules of thumb. Since there is no single accepted definition for what constitutes an effective security system for a critical facility and how best to design and analyse these systems, this technical note is a survey of potential metrics and methods for critical facility system effectiveness. Recommendations are made for which metric is best suited for critical facility system effectiveness and a new method is recommended for evaluating system effectiveness.

Using agent technology to move from intention-based to effect-based models

Following current modeling paradigms, most processes are captured in the form of modeling a desired intent, often using success probabilities. In addition, only special roles that entities are intended to play are modeled. For effect-based modeling, the unintended but nonetheless resulting effects are as important as the intended effects, and they are therefore modeled. Also, un inspected actions based on alternative roles are important. Using agents to not only represent influencers and targets but also the processes, it becomes possible to capture all effects and move from ¿what I intended to accomplish¿ to ¿what I really accomplished,¿ including side and secondary effects. The agent architecture and a prototype for this effect-based model are presented in this paper.

Accounting for Errors when using Systems Approaches

Complex systems problems require the use of a formal philosophical construct and dictate the use of a rigorous systems approach. A systems approach may utilize one of a variety of proven methods, but in each case it involves the imposition of order that ranges from the philosophical to the procedural. Independent of the construct or rigor used to address the complex systems problem is the opportunity to commit a number of errors as part of a systems approach. This paper will discuss six classifications for problem solving errors that may be experienced during the application of a systems approach as part of understanding and treating complex systems problems.

Determining Stakeholder Influence Using Input-output Modeling☆

Abstract Stakeholders are a vital element in all complex systems problems. They are customers, users, clients, suppliers, employees, and team members. They fund the system, design it, build it, operate it, use it, maintain it, and dispose of it. While many approaches exist for classifying and determining their attitudes, these approaches stop short of evaluating stakeholders in a holistic manner. This paper closes this research gap by developing the metric of stakeholder situation influence, a measure which allows for quantitative evaluation of stakeholder influence on a given problem. This measure is derived from Leontief Input-Output analysis. The developed approach extends previous work by the authors to showcase how stakeholders may be mapped holistically in a manner that serves to improve scenario situational awareness and support resource allocation decisions.