Megan Hoarfrost

Bio: Megan Hoarfrost is an academic researcher from Portland State University. The author has contributed to research in topics: Model-based testing. The author has an hindex of 1, co-authored 1 publications receiving 8 citations.

The case for thoroughly testing complex system dynamic models

Abstract: The Case for Thoroughly Testing Complex System Dynamics Models Wayne Wakeland and Megan Hoarfrost 1 Systems Science Ph.D. Program, Portland State University 2 Stanford University 1 P.O. Box 751, Portland, OR 97207 (503) 725-4975(v) (503) 725-8489 (f) wakeland@pdx.edu Abstract In order to determine whether model testing is as useful as suggested by modeling experts, the full battery of model tests recommended by Forrester, Senge, Sterman, and others was applied retrospectively to a complex previously-published system dynamics model. The time required to carry out each type of test was captured, and the benefits that resulted from applying each test was determined subjectively. The resulting benefit to cost ratios are reported. These ratios suggest that rather than focusing primarily on sensitivity testing, modelers should consider other types of model tests such as extreme condition tests and family member tests. The study also finds that all of the different kinds of tests were either moderately useful or very useful--fully supporting the recommendations of the experts.

Modeling and simulating causal dependencies on process-aware information systems from a cost perspective

Abstract: Providing effective IT support for business processes has become crucial for enterprises to stay competitive in their market. Business processes must be defined, implemented, enacted, monitored, and continuously adapted to changing situations. Process life cycle support and continuous process improvement become critical success factors in contemporary and future enterprise computing. In this context, process-aware information systems (PAIS) adopt a key role. Thereby, organization-specific and generic process support systems are distinguished. In the former case, the PAIS is build "from scratch" and incorporates organization-specific information about the structure and processes to be supported. In the latter case, the PAIS does not contain any information about the structure and processes of a particular organization. Instead, an organization needs to configure the PAIS by specifying processes, organizational entities, and business objects. To enable the realization of PAIS, numerous process support paradigms, process modeling standards, and business process management tools have been introduced. The application of these approaches in PAIS engineering projects is not only influenced by technological, but also by organizational and project-specific factors. Between these factors there exist numerous causal dependencies, which, in turn, often lead to complex and unexpected effects in PAIS engineering projects. In particular, the costs of PAIS engineering projects are significantly influenced by these causal dependencies. What is therefore needed is a comprehensive approach enabling PAIS engineers to systematically investigate these causal dependencies as well as their impact on the costs of PAIS engineering projects. Existing economic-driven IT evaluation and software cost estimation approaches, however, are unable to take into account causal dependencies and resulting effects. In response, this thesis introduces the EcoPOST framework. This framework utilizes evaluation models to describe the interplay of technological, organizational, and projectspecific evaluation factors, and simulation concepts to unfold the dynamic behavior of PAIS engineering projects. In this context, the EcoPOST framework also supports the reuse of evaluation models based on a library of generic, predefined evaluation patterns and also provides governing guidelines (e.g., model design guidelines) which enhance the transfer of the EcoPOST framework into practice. Tool support is available as well. Finally, we present the results of two online surveys, three case studies, and one controlled software experiment. Based on these empirical and experimental research activities, we are able to validate evaluation concepts underlying the EcoPOST framework and additionally demonstrate its practical applicability.

System dynamics model of cervical cancer vaccination and screening interventions in Kenya

Abstract: This paper presents a simulation model for evaluating the possible effects of a screening and vaccination campaign against Human Papillomavirus [HPV] in Kenya. A System Dynamics model was developed using the iThink™ computer simulation package. The model was based on data extracted from epidemiological, demographic and published research and where data was not available, expert opinion was sought. The deterministic model stratified the population by vaccination status, screening status and HPV infection status. The model was simulated to estimate outputs for the next 50 years from 2011. Cost Utility indicators of Disability Adjusted Life Years (DALYs) and cost per averted DALY were used for economic evaluation. The model predicted that catch up vaccination had the greatest impact in reducing the prevalence of cervical cancer. This was followed by Primary vaccination, with early detection through Screening having the lowest impact of the three choices of interventions in respect of averted cases of cervical cancer and DALY estimates. Kenya as a country should consider adoption of secondary /catch up vaccination as an immediate measure to curb cervical cancer followed by primary vaccination of pre-adolescent girls. Screening should be a complementary measure(s). This model provides a policy decision support vehicle that can allow for choice between different interventions based on their expected outcomes. It also allows modification to accommodate new research results and information to assess the clinical impact of different policies and interventions in cervical cancer management in Kenya.

Understanding laborers' behavioral diversities in multinational construction projects using integrated simulation approach

Abstract: Employing multi-type laborers (MLs) is common in multinational and cross-culture projects (MPCs). Different attributes of MLs can lead to uncertain and dynamic laborer behaviors (i.e. behavioral diversities), which may cause project deviations. Previous studies do not consider the uncertainties or dynamics of behaviors adequately or they only provide general suggestions. The purpose of this paper is to combine system dynamics (SD) and agent-based modeling (ABM) to build an integrated model. The proposed ABM-SD can gain better understanding of MLs’ behavioral diversities, reveal the associated impacts and improve project management.,Based on extensively review in construction labor management and computer simulation, architecture is built to depict the relationships between the affecting factors of MLs’ behaviors, MLs’ behavioral diversities and project performance. Second, conceptual structures of the ABM-SD model are developed. Third, methods to implement the model in practice are introduced, focusing on data collection and model structure adjustment. Finally, the model is tested in a case study.,Different ML groups have distinctive behaviors which constantly change through interactions between MLs, engineers and external environment. Inadequate consideration of the diversities can result in inaccurate estimation of productivity, work quality and absenteeism, causing severe project deviations such as schedule delay, cost overrun and high absenteeism. On the other hand, using the ABM-SD model, the root causes of project deviations are analyzed from the perspective of MLs’ behavioral diversities and the optimization of labor management can significantly improve project performance.,This paper supplements previous studies because the ABM-SD model takes fully use of the strength of simulation of solving uncertain and dynamic problems and combines both qualitative and quantitative findings in existing studies of labor management. Besides, the ABM-SD model is also a practical management tool to better monitor laborer behaviors and forecast the impacts. The limitation is mainly about the small scale of the case study. However, the ABM-SD model already demonstrates the mechanism about how MLs’ different behaviors affect a project, which fulfill the aim of the study.,The ABM-SD model can simulate MLs’ behavioral diversities and produce reliable estimations of project performance. It also allows to optimize management plans. Furthermore, The ABM-SD model is adjustable based on specific project conditions, which make it applicable for different tasks, different laborer compositions and even different projects. Thus, the ABM-SD model can be a practical tool for engineers in MCPs.,SD and ABM are applied to study behaviors with well-known benefits in both separated and integrated manner. However, few studies use the approach to investigate MLs’ behaviors in MCPs. Hence, the proposed ABM-SD model is an original attempt to improve the laborer management level in MCPs.

Group Model Validation

Abstract: In this paper we report if and how validation is integrated in the different participatory approaches in System Dynamics. After this we present an analysis of 86 case studies to create a picture of how validation is conducted and reported in the field. We found that validation is hardly described as an integrated part of any participatory modeling approach. Furthermore, the process of validation and the end-result is little reported on in any case study. We believe that there is a significant difference between validation in non-participatory and participatory approaches due to the social aspect. In this context we derive three questions as a requirement for validation. The aim is balancing individual mental models, group mental models and logic and data. Based on the tension between these three factors we developed a preliminary approach to participatory structure validation. This procedure is focused on generating a productive amount of cognitive conflict in order to confront the structure of the model with all available information. The outcome is increased structure validity, documentation of limitations and increased understanding of the reasoning underlying the model's structure. Word count: 5292 (without references, appendices and abstract)