Decision makers\u27 experience of participatory dynamic simulation modelling: Methods for public health policy

Background: Systems science methods such as dynamic simulation modelling are well suited to address questions about public health policy as they consider the complexity, context and dynamic nature of system-wide behaviours. Advances in technology have led to increased accessibility and interest in systems methods to address complex health policy issues. However, the involvement of policy decision makers in health-related simulation model development has been lacking. Where end-users have been included, there has been limited examination of their experience of the participatory modelling process and their views about the utility of the findings. This paper reports the experience of end-user decision makers, including senior public health policy makers and health service providers, who participated in three participatory simulation modelling for health policy case studies (alcohol related harm, childhood obesity prevention, diabetes in pregnancy), and their perceptions of the value and efficacy of this method in an applied health sector context. Methods: Semi-structured interviews were conducted with end-user participants from three participatory simulation modelling case studies in Australian real-world policy settings. Interviewees were employees of government agencies with jurisdiction over policy and program decisions and were purposively selected to include perspectives at different stages of model development. Results: The ‘co-production’ aspect of the participatory approach was highly valued. It was reported as an essential component of building understanding of the modelling process, and thus trust in the model and its outputs as a decision-support tool. The unique benefits of simulation modelling included its capacity to explore interactions of risk factors and combined interventions, and the impact of scaling up interventions. Participants also valued simulating new interventions prior to implementation in the real world, and the comprehensive mapping of evidence and its gaps to prioritise future research. The participatory aspect of simulation modelling was time and resource intensive and therefore most suited to high priority complex topics with contested options for intervening. Conclusion: These findings highlight the value of a participatory approach to dynamic simulation modelling to support its utility in applied health policy settings

Impact of model fidelity in factory layout assessment using immersive discrete event simulation

Discrete Event Simulation (DES) can help speed up the layout design process. It offers further benefits when combined with Virtual Reality (VR). The latest technology, Immersive Virtual Reality (IVR), immerses users in virtual prototypes of their manufacturing plants to-be, potentially helping decision-making. This work seeks to evaluate the impact of visual fidelity, which refers to the degree to which objects in VR conforms to the real world, using an IVR visualisation of the DES model of an actual shop floor. User studies are performed using scenarios populated with low- and high-fidelity models. Study participant carried out four tasks representative of layout decision-making. Limitations of existing IVR technology was found to cause motion sickness. The results indicate with the particular group of naïve modellers used that there is no significant difference in benefits between low and high fidelity, suggesting that low fidelity VR models may be more cost-effective for this group

Inducing Low-Carbon Investment in the Electric Power Industry through a Price Floor for Emissions Trading

Uncertainty about long-term climate policy is a major driving force in the evolution of the carbon market price. Since this price enters the investment decision process of regulated firms, this uncertainty increases the cost of capital for investors and might deter invest-ments into new technologies at the company level. We apply a real options-based approach to assess the impact of climate change policy in the form of a constant or growing price floor on investment decisions of a single firm in a competitive environment. This firm has the opportunity to switch from a high-carbon “dirty” technology to a low-carbon “clean” technology. Using Monte Carlo simulation and dynamic programming techniques for real market data, we determine the optimal CO2 price floor level and growth rate in order to induce investments into the low-carbon technology. We show these findings to be robust to a large variety of input parameter settings.Carbon price, price floor, technological change, investment decision, real option approach

The Usage of the PALISADE Program Pack in the Process of Substantiation and Adoption of Decisions

In the actual society of knowledge, the impact of the new informational technologies was extended even in an important domain of human activity: the adoption of decisions. The necessity of objecting at the selection process of the most favorable decision lead to the extension of the usage of information technology also in the conceptual phase. The decision tools suite (DTS) and the expert systems have the answer for the computer science workers at the needs of the deciders, used especially in the case of the decisions adopted in conditions of risk or uncertainty. The PALISADE package of programmers is a support system of decisions, which overlaps the processor tables, increasing the possibility of usage, especially for simulation problems, calculating the risk, building decision trees etc.Palisade, risk, decision, analysis

The value of simulation and immersive virtual reality environments to design decision making in new product development

In response to the need to develop more sophisticated, higher quality products product developers are more and more expecting engineering simulations to provide them with the data, information, and knowledge required to make design decisions. Engineering simulations provide insight into the behaviour of virtual product designs and have the capacity to be executed many thousands of times to provide a comprehensive coverage of the solution space being explored. However, engineering simulations are only representative of a reduced set of product properties and are bound by the constraints imposed by the fidelity of the underlying physics of the simulation tools being used. In this paper, we will briefly explore a number of different types of engineering simulation that the Virtual Engineering Centre has been involved in creating and consider the value that the data, information and knowledge that each creates to the decision making process. We will also explore how different visualisation methods being used at the Virtual Engineering Centre support decision making by individuals and groups of people in a design review context. Specifically, we will discuss the use of immersive virtual reality in reviewing simulation results and highlight the limitations of using this technology in group decision making using a case study taken from our work with Bentley Motors. We will conclude that whilst virtual technologies provide opportunities to generate data and information early in the product development process, the ever increasing demands for accuracy and fidelity in representation in mature product sectors outstrips the capability of the technology to fully support decision making in a complete virtual world

Methods for Utilizing Connected Vehicle Data in Support of Traffic Bottleneck Management

The decision to select the best Intelligent Transportation System (ITS) technologies from available options has always been a challenging task. The availability of connected vehicle/automated vehicle (CV/AV) technologies in the near future is expected to add to the complexity of the ITS investment decision-making process. The goal of this research is to develop a multi-criteria decision-making analysis (MCDA) framework to support traffic agencies’ decision-making process with consideration of CV/AV technologies. The decision to select between technology alternatives is based on identified performance measures and criteria, and constraints associated with each technology. Methods inspired by the literature were developed for incident/bottleneck detection and back-of-queue (BOQ) estimation and warning based on connected vehicle (CV) technologies. The mobility benefits of incident/bottleneck detection with different technologies were assessed using microscopic simulation. The performance of technology alternatives was assessed using simulated CV and traffic detector data in a microscopic simulation environment to be used in the proposed MCDA method for the purpose of alternative selection. In addition to assessing performance measures, there are a number of constraints and risks that need to be assessed in the alternative selection process. Traditional alternative analyses based on deterministic return on investment analysis are unable to capture the risks and uncertainties associated with the investment problem. This research utilizes a combination of a stochastic return on investment and a multi-criteria decision analysis method referred to as the Analytical Hierarchy Process (AHP) to select between ITS deployment alternatives considering emerging technologies. The approach is applied to an ITS investment case study to support freeway bottleneck management. The results of this dissertation indicate that utilizing CV data for freeway segments is significantly more cost-effective than using point detectors in detecting incidents and providing travel time estimates one year after CV technology becomes mandatory for all new vehicles and for corridors with moderate to heavy traffic. However, for corridors with light, there is a probability of CV deployment not being effective in the first few years due to low measurement reliability of travel times and high latency of incident detection, associated with smaller sample sizes of the collected data

Student interactions in online discussion forums: their perception on learning with business simulation games

Digital technology offers new teaching methods with controversial results over learning. They allow students to develop a more active participation in their learning process although it does not always drive to unequivocal better learning outcomes. This study aims to offer additional evidence on the contribution of business simulation games to students' learning outcomes, considering student interactions in online discussion forums. We conducted a qualitative research with the online discussion forums of 5 different courses at bachelor and master levels, which involves 41 students' teams. The final sample was composed of 3681 messages posted by the students. The results reveal that some generic and specific managerial skills exert a positive influence on learning outcomes. Students mostly highlighted teamwork, decision-making, information processing, reaching agreements, and dealing with uncertainty as the most relevant contributions of the game towards their learning. These results have instructional and pedagogical implications for determining the best way to enhance students' motivation and learning outcomes when using digital technology methods, which involves recommendations that affect their design and monitoring

Modelling & Simulation as a Strategic Tool for Decision-Making Process: A Dairy Case Study

The Dairy Industry faces many challenges compared to other sectors. On the supply side due to the nature of the raw material, large inventories are not applied; during the manufacturing process, the continuous production is highly sensitive to any sort of unplanned disruption; and on the demand side, the market dictates the commodity prices. In response to the growth in competition, dairy organizations’ strategy must incorporate technology into their daily processes in order to become more efficient, profitable and sustainable. To achieve desired levels of improvement, Modelling and Simulation has been increasing in popularity in the decision-making process. Using a Dairy company as a case study, this paper has highlighted the potential for Modelling and Simulation to be used as a powerful strategic tool for decision-making processes