David F. Andersen

Scripts for group model building

Building models directly with client groups has become increasingly common in the field of system dynamics. For the past nine years, the modeling group at the University at Albany has been experimenting with techniques handling the complex modeling and facilitation processes involved in group work. This article extends the previously reported work by discussing specific scripted techniques used to implement the group modeling building approach. The authors’ purpose is to initiate a larger discussion of shared scripts and techniques for group model building. The discussion is divided into planning for a group model building conference, scheduling the day, particular scripts and techniques for various group model building tasks, and closing a group modeling conference.

Group model building: adding more science to the craft

This article discusses the issue of making group model building interventions more of a science than an art by outlining a number of requirements of a research program. Important elements that are discussed are the various goals of group model building interventions and the components and scripts of an intervention. Then the problem of theory development is discussed, together with a number of hypotheses which the authors suggest need more investigation. The article also discusses issues related to the selection of an appropriate research design, as well as a number of thorny measurement problems.

Group model building: problem structuring, policy simulation and decision support

The authors use the term, ‘Group Model Building’ (GMB) (Richardson and Andersen, 1995; Vennix, 1996, 1999) to refer to a bundle of techniques used to construct system dynamics models working direct...

Model-building for group decision support: Issues and alternatives in knowledge elicitation

Abstract System dynamics models are often created using multiple streams of information including quantitative data, written records, and information contained in the mental models of both individuals and groups. While qualitative sources of information are widely recognized as important in all stages of the model-building process, little systematic research has been completed on how best to elicit and map this knowledge from groups of experts. In this article, we survey the existing literature on mapping and eliciting knowledge for system dynamics modeling and also explore the literature in the broader fields of cognitive psychology and small group processes. Special attention is paid to new software advances to support these processes. Two case studies illustrate how these knowledge-eliciting techniques can be used to support the construction of computer simulation models.

A framework for evaluating systems thinking interventions: an experimental approach to mental health system change

Researchers from the State University of New York at Albany and the New York State Office of Mental Health have been engaged in testing an experimental approach to evaluating systems thinking interventions. This research calls for a similar systems thinking intervention to be repeated in four counties with four control counties also selected and observed via pre- and post-intervention measures. The overall context of the project focuses on integration of mental health and vocational rehabilitation services. The experiment is designed to evaluate measurable outcomes, including shifts in goal structures and change strategies of the management team, shifts in relative alignment of the management team as a whole, perceived success of the intervention, and changes in systems and procedures necessary to improve client services. This article presents a framework for evaluating systems thinking interventions as well as preliminary findings from the pilot test.

A behavioral theory of insider-threat risks: A system dynamics approach

The authors describe a behavioral theory of the dynamics of insider-threat risks. Drawing on data related to information technology security violations and on a case study created to explain the dynamics observed in that data, the authors constructed a system dynamics model of a theory of the development of insider-threat risks and conducted numerical simulations to explore the parameter and response spaces of the model. By examining several scenarios in which attention to events, increased judging capabilities, better information, and training activities are simulated, the authors theorize about why information technology security effectiveness changes over time. The simulation results argue against the common presumption that increased security comes at the cost of reduced production.

Integrating modes of policy analysis and strategic management practice : requisite elements and dilemmas

There is a need to bring methods to bear on public problems that are inclusive, analytic, and quick. This paper describes the efforts of three pairs of academics working from three different though complementary theoretical foundations and intervention backgrounds (ie ways of working) who set out together to meet this challenge. Each of the three pairs had conducted dozens of interventions that had been regarded as successful or very successful by the client groups in dealing with complex policy and strategic problems. One approach focused on leadership issues and stakeholders, another on negotiating competitive strategic intent with attention to stakeholder responses, and the third on analysis of feedback ramifications in developing policies. This paper describes the 10-year longitudinal research project designed to address the above challenge. The important outcomes are reported: the requisite elements of a general integrated approach and the enduring puzzles and tensions that arose from seeking to design a wide-ranging multi-method approach.

Eliciting Group Knowledge for Model-Building

System dynamics models are typically created using multiple streams of information including quantitative data, written records, and information contained in the mental models of both individuals and groups. While qualitative sources of information are widely recognized as important in all stages of the model building process, little systematic research has been completed on how best to elicit and map this knowledge. In this paper, we survey the existing literature on mapping and eliciting knowledge for system dynamics modeling and also explore the literature in the broader fields of cognitive psychology and small group processes. Special attention is paid to new software advances to support these processes.2

Modeling intergovernmental collaboration: a system dynamics approach

Describes the development and testing of a system-dynamics model of collaboration, trust-building and knowledge sharing in a complex, inter-governmental information system project. The model-building and testing activity was an exploration of the feasibility of applying these modeling methods to a complex inter-organizational process about which only qualitative data were available. The process to be modeled was the subject of qualitative field research studying knowledge and information sharing in inter-organizational networks. This research had produced a large volume of observational and interview data and analyses about the technology project. In the course of collecting and analyzing data from this project, the researchers noted evidence of what appeared to be important feedback effects. The feedback loops appeared to influence the collaboration and knowledge sharing, critical parts of how the information system design and construction progressed. These observations led to conversations with colleagues who had extensive experience in dynamic modeling. All agreed that applying dynamic modeling methods to this process had considerable potential to yield valuable insights into collaboration. As a novel application of the methods, it could yield new modeling insights as well. The modeling experience supported both propositions and was judged a success that will lead to continued exploration of these questions.

Some conceptual and technical problems in integrating models of judgment with simulation models

Recent research has focused on how policy makers learn from and make better use of policy-oriented simulation models. It is proposed that those who construct simulation models make simplifying assumptions concerning the wide range of judgment tasks that surround both model building and decision making in real policy contexts. Linking formal judgment models with formal simulation models has been suggested as an approach to dealing with those simplifications. A demonstration experiment that illustrates how simulation models and models of human judgment explicitly can be linked within a unified framework is presented. In creating this linkage six important conceptual and technical problems are encountered and discussed. While many of the technical problems are believed to result from the specific approaches used in the study, the broader conceptual problems are believed to persist, even if differing methods are used. >