Fifty years of systems thinking for management

The point of this paper is to provide an account of the last 50 years of systems thinking applied to management that is insightful and useful to those interested in the theory and practice of operational research (OR). In seeking to fulfil this purpose, it employs Boulding's well-known ‘hierarchy of complexity’ to think through the reasons for the emergence of different strands of applied systems thinking and to detail their strengths. In theoretical terms, operational researchers will find a number of the key issues that have engaged their field (eg, hard versus soft approaches) mirrored in debates that have taken place between systems thinkers. They may discover new theoretical avenues to follow to advance their discipline. OR practitioners may also be surprised by the nature and scope of the systems applications described and conclude that systems approaches should be added to their own intervention strategies. At the least, the paper is designed to reinvigorate discussion around the relationship between OR and systems thinking that has occasionally surfaced over the last half century but has never been satisfactorily concluded.     

Degenerate integrable systems on the plane with a cubic integral of motion

We propose a classification of the known two-dimensional Hamiltonian systems of the natural form possessing an additional integral of motion that is cubic in the momenta. For degenerate systems of the Stäckel type, the additional cubic integral has the form of a “generalized angular momentum”. This allows constructing n-dimensional degenerate systems of the Stäckel type with additional cubic integrals of motion.     

Evaluating systems thinking in housing

This paper describes and evaluates work carried out in the social housing context in the United Kingdom using a systems thinking approach called ‘lean systems’ (LS). The work, sponsored by the Office of the Deputy Prime Minister, was designed to test whether LS could improve the efficiency of delivery of housing management and maintenance services. A pilot programme was developed in which three housing organizations used the approach in different service areas. The results indicate that LS can yield efficiency gains and improvements in service performance, customer satisfaction and staff morale—although securing and sustaining these results requires considerable organizational commitment. The LS approach is outlined, work in the pilots described and the results presented. A theoretical analysis seeks to locate LS in the spectrum of systems methodologies and to delimit its particular area of competence.     

Multiscale decision-making: Bridging organizational scales in systems with distributed decision-makers

Decision-making in organizations is complex due to interdependencies among decision-makers (agents) within and across organizational hierarchies. We propose a multiscale decision-making model that captures and analyzes multiscale agent interactions in large, distributed decision-making systems. In general, multiscale systems exhibit phenomena that are coupled through various temporal, spatial and organizational scales. Our model focuses on the organizational scale and provides analytic, closed-form solutions which enable agents across all organizational scales to select a best course of action. By setting an optimal intensity level for agent interactions, an organizational designer can align the choices of self-interested agents with the overall goals of the organization. Moreover, our results demonstrate when local and aggregate information exchange is sufficient for system-wide optimal decision-making. We motivate the model and illustrate its capabilities using a manufacturing enterprise example.     

Critical systems thinking and practice

Critical systems thinking and the methodologies associated with it were developed precisely to allow analysis of complex societal problems and intervention to resolve such problems. Early approaches employing systems ideas, such as operational research, systems analysis and systems engineering, were suitable for tackling certain well-defined problems, but were found to have limitations when faced with complex problems involving people with a variety of viewpoints and frequently at odds with one another. Systems thinkers responded with approaches such as system dynamics and organisational cybernetics to tackle complexity; soft systems methodology (SSM) and interactive planning to handle subjectivity; and critical systems heuristics to help the disadvantaged in situations involving conflict. There was a corresponding enlargement of the range of problem contexts in which they felt competent to intervene. It has been critical systems thinking, however, which has supplied the bigger picture, has allowed systems thinking to mature as a discipline and has set out how the variety of methodologies now available can be used together in a coherent manner to promote successful intervention in complex societal problem situations. This paper outlines, at the request of the editor of this special issue, my involvement in developing critical systems thinking and practice, describes its origins, nature and use, and sets out a programme for future research in the area.     

On maximally superintegrable systems

Locally any completely integrable system is maximally superintegrable system since we have the necessary number of the action-angle variables. The main problem is the construction of the single-valued additional integrals of motion on the whole phase space by using these multi-valued action-angle variables. Some constructions of the additional integrals of motion for the Stäckel systems and for the integrable systems related with two different quadratic r-matrix algebras are discussed. Among these system there are the open Heisenberg magnet and the open Toda lattices associated with the different root systems.     

DOES COMPETENCY-BASED TRUST BENEFIT ORGANIZATIONAL PERFORMANCE—A MESO EXPLORATION USING COMPUTER MODELING

From a competency-based perspective of trust and an open system's view of organizations, this study explores the micro-macro linkage between interpersonal trust and organizational performance in work organizations where internal and external contexts can matter. With the help of a formal computer model for meso theorizing, this study shows that competency-based trust generally does not benefit organizational performance in a distributed decision-making setting, except under incorrect information conditions or when no formal procedure is available. The study further demonstrates that external environments, organizational structures, and internal operating conditions can all moderate such trust-performance relationships. Findings from this study suggest the need for new thinking relating to trust in organizations and the possibility to integrate psychological, economic, and sociological perspectives on trust.     

Broadening the boundaries: an application of critical systems thinking to IS planning in Colombia

Most current information systems (IS) planning methodologies are focused on achieving plans that provide competitive advantage to business and solve the problems of information needs by using the latest technologies available. This paper presents an alternative approach to IS planning based on critical systems thinking—a research perspective that encourages the analysis of stakeholders' understandings of social contexts prior to the selection and/or design of planning methods. The approach is underpinned by a combination of the systems theories of autopoiesis and boundary critique, and it enables participants to reflect on different concerns and values during IS planning. This approach was applied in a project with a Colombian University, and it helped participants to uncover and address important human issues not usually seen as relevant by traditional approaches to IS planning. In addition, it led the authors to undertake further research on ethics after the project had been concluded.     

Homogeneous Stäckel-type systems

A class of Hamiltonian dynamic systems integrated by the variable separation method is considered. The integration for this class is the inversion of an Abel mapping on hyperelliptic curves. We prove that the derivative of the Abel mapping is the Stäckel matrix, which determines a diagonal Riemannian metric and curvilinear orthogonal coordinate systems in a flat space. Lax representations with the spectral parameter are constructed. The corresponding classicalr-matrices are dynamic. It is shown how the class of pointwise canonical transformations can be naturally generalized using the Abel integral reduction theory.     

Ergodic theorems for queuing systems with dependent inter-arrival times

We study a G/GI/1 single-server queuing model with i.i.d. service times that are independent of a stationary process of inter-arrival times. We show that the distribution of the waiting time converges to a stationary law as time tends to infinity provided that inter-arrival times satisfy a Gärtner-Ellis type condition. A convergence rate is given and a law of large numbers established. These results provide tools for the statistical analysis of such systems, transcending the standard case with independent inter-arrival times.     

Changes in belief systems,quality of life issues and social conditions over 25 years in post-war Japan

Summary The data, which are analyzed in the paper, are based on the continuing nation wide random sample surveys which have been conducted every five years over 25 years since 1953 in Japan by the Research Committee on the Study of Japanese National Character of the Institute of Statistical Mathematics. The importance of the changes in belief systems and ways of thinking is insisted. It is remarked that only the simple tabulations by various breakdowns and simple cross-tabulations among the 2 or 3 questions do not always reveal the changes of belief systems and ways of thinking. The statistical method of principal component analysis of categorical data, which is called theory of quantification of response pattern (quantification method III) and equivalent to Benzécri's correspondence analysis, is effectively adopted to reveal them. The consistency and the features of change of them over 25 years in post-war Japan emerge. This paper also gives useful examples how to use the quantification method III. Data in this paper were obtained in the various surveys conducted by the Research Committee on the Study of the Japanese National Character. The members of the Committee are Chikio Hayashi (chairman), Sigeki Nisihira, Tatsuzo Suzuki, Kinji Mizuno, Yosiyuki Sakamoto, Giichiro Suzuki, Masakatsu Murakami and Hirojiro Aoyama. The Institute of Statistical Mathematics     

Noncanonical time transformations relating finite-dimensional integrable systems

We consider dual Stäckel schemes related to each other by a noncanonical transformation of the time variable. We prove that this duality of different integrable systems arises from the multivaluedness of the Abel mapping. We construct the Lax matrices and the r-matrix algebras for some integrable systems on a plane. The integrable deformations of the Kepler problem and the Holt-type systems are considered in detail.     

Multi-Agent Social and Organizational Modeling of Electric Power and Natural Gas Markets

Complex Adaptive Systems (CAS) can be applied to investigate large-scale socio-cognitive-technical systems. Viewing such systems from a multi-agent social and organizational perspective allows innovative computational policy analysis. Argonne National Laboratory (ANL) has taken such a perspective to produce an integrated model of the electric power and natural gas markets. This model focuses on the organizational interdependencies between these markets. These organizational interdependencies are being strained by fundamental market transformations.     

Representational systems,learning, and problem solving in mathematics

This article explores aspects of a unified psychological model for mathematical learning and problem solving, based on several different types of representational systems and their stages of development. The goal is to arrive at a scientifically adequate theoretical framework, complex enough to account for diverse empirical results but sufficiently simple to be accessible and useful in mathematics education practice. Some perspectives on representational systems are discussed, and components of the model are described in relation to these ideas—including constructs related to imagistic thinking, heuristics and strategies, affect, and the fundamental role of ambiguity.     

A review of the recent contribution of systems thinking to operational research and management science

The systems approach, or systems thinking, has been intimately connected with the development of OR and management science initially through the work of founders such as Churchman and Ackoff and latterly through innovations such as soft systems. In this paper we have undertaken a review of the contribution that systems thinking has been making more recently, especially to the practice of OR. Systems thinking is a discipline in its own right, with many theoretical and methodological developments, but it is also applicable to almost any problem area because of its generality, and so such a review must always be selective. We have looked at the literature from both a theoretical and an applications orientation. In the first part we consider the main systems theories and methodologies in terms of their recent developments and also their applications. This covers: the systems approach, complexity theory, cybernetics, system dynamics, soft OR and PSMs, critical systems and multimethodology. In the second part we review the main domains of application: strategy, information systems, organisations, production and operations, ecology and agriculture, and medicine and health. Our overall conclusion is that while systems may not be well established institutionally, in terms of academic departments, it is incredibly healthy in terms of the quantity and variety of its applications.     

Neural networks and organizational systems: Modeling non-linear relationships

For decades, organizational researchers have employed standard statistical methods to uncover relationships among variables and constructs. However, in complex organization systems, the prevalence of non-linearity and outliers is to be expected. Under such circumstances, the use of standard statistical methods becomes unreliable and, correspondingly, results in degraded predictions of the relationships within the organizational systems. We describe the use of neural network analyses to model team effectiveness so as to provide more accurate predictions for managers.     

On existence of periodic solutions for gradient systems with applications

In this paper we prove the existence of periodic solutions for gradient systems in finite and infinite dimensional spaces. The techniques of the proofs are based on the application of a global inverse functions theorem, the Schäefer fixed point theorem and the Faedou–Galerkin method. We apply our results in order to solve nonlinear reaction–diffusion equations with Dirichlet and Neumann boundary conditions.     

The SEXTANT software: A tool for automating the comparative analysis of mental models of dynamic systems

The comparison of mental models of dynamic systems improves our understanding of how people comprehend, interpret, and subsequently influence dynamic management tasks. Approaches to comparing mental models currently used in managerial and organizational cognition research, especially the distance-ratio and the closeness-approaches, have been criticized for not considering essential characteristics of dynamic managerial situations. This paper builds on a recent analysis method developed to compare mental models of dynamics systems, and introduces this mathematical approach to management and organizational researchers by means of the SEXTANT software. It presents the process of mental model elicitation, analysis, comparison, and interpretation. An example with four elicited mental models illustrates the software’s features to analyze and present the results. Then, the software is compared with existing software to map and compare mental models. Our conclusion is that SEXTANT marks a significant step in enabling large-scale studies about mental models of dynamic systems.     

Analysis,modeling, emergence & integration in complex systems: A modeling and integration framework & system biology

Analysis and Modeling is the first “phase” of understanding or developing a system. It is also, maybe more importantly, the foundation of understanding a natural science or system. It's abstract and conceptually difficult but, being foundational, contributes the most to the quality of understanding of (designed or natural) systems. Complex Systems have a natural hierarchy of levels and multiple subsystems. The character and functionality of each level or subsystem “emerges” across its boundaries. Both sides of these boundaries must be understood within that side's natural thought patterns. Integrated interdisciplinary collaboration is essential for making sense of complex systems; but collaboration among disciplines is difficult, because of their different ways of thinking. This creates a dilemma, “understanding complex systems” is one horn; “integrated interdisciplinary collaboration” is the other. This dilemma in complex system analysis/modeling and interdiscipline collaboration, is currently addressed by “grabbing the bull by the horns.” This takes on this doubly complex problem, by painstakingly building up abstract “bull wrestling” skills in and across domains and disciplines. There's another wrinkle; complexity requires interdisciplinary collaboration at deeper, more dissimilar, levels. The usual approach, finding a way to “pass between the horns of the dilemma” will not work here, due to this cross coupling. Rather than trying to pass between the horns, by abstracting away the coupling, we overtly organizing this coupling. We weave a semantic unification space of conceptual connections linking each side of a boundary to its appropriate way of thinking. This allows us to abstracting away the dilemma and iron out the wrinkle. The threads of common image schemas, cognitive metaphors and conceptual interfaces, weave a bridge between the semantics foundations and organizations of each problem. These allow addressing the problems synergistically. This paper presents and explores a naturally valid way for discipline specific and discipline integrating addressing complex systems. We start with the methodological insights from analysis and modeling from the perspective of object orientation, with its ontologies, organizing lexical semantics. We advance from there by integrating in imagistic, imaginative semantics and affordance based interaction methodology, as the keys to addressing complex systems analysis, modeling and integration. © 2007 Wiley Periodicals, Inc. Complexity, 2007