Promoting articulated action from diverse stakeholders in response to public policy scenarios: A case analysis of the use of ‘scenario improvisation’ method

In this paper we present a novel application of scenario methods to engage a diverse constituency of senior stakeholders, with limited time availability, in debate to inform planning and policy development. Our case study project explores post-carbon futures for the Latrobe Valley region of the Australian state of Victoria. Our approach involved initial deductive development of two ‘extreme scenarios’ by a multi-disciplinary research team, based upon an extensive research programme. Over four workshops with the stakeholder constituency, these initial scenarios were discussed, challenged, refined and expanded through an inductive process, whereby participants took ‘ownership’ of a final set of three scenarios. These were both comfortable and challenging to them. The outcomes of this process subsequently informed public policy development for the region. Whilst this process did not follow a single extant structured, multi-stage scenario approach, neither was it devoid of form. Here, we seek to theorise and codify elements of our process – which we term ‘scenario improvisation’ – such that others may adopt it.

A decision-analysis-based framework for analysing stakeholder behaviour in scenario planning

Scenario planning is a method widely used by strategic planners to address uncertainty about the future. However, current methods either fail to address the future behaviour and impact of stakeholders or they treat the role of stakeholders informally. We present a practical decision-analysis-based methodology for analysing stakeholder objectives and likely behaviour within contested unfolding futures. We address issues of power, interest, and commitment to achieve desired outcomes across a broad stakeholder constituency. Drawing on frameworks for corporate social responsibility (CSR), we provide an illustrative example of our approach to analyse a complex contested issue that crosses geographic, organisational and cultural boundaries. Whilst strategies can be developed by individual organisations that consider the interests of others – for example in consideration of an organisation's CSR agenda – we show that our augmentation of scenario method provides a further, nuanced, analysis of the power and objectives of all concerned stakeholders across a variety of unfolding futures. The resulting modelling framework is intended to yield insights and hence more informed decision making by individual stakeholders or regulators.

scenario-focused development method for a pen-based user interface: model and applications

Pen-based user interface (PUI) has drawn significant interest, owing to its intuitiveness and convenience. While much of the research focuses on the technology, the usability of a PUI has been relatively low since human factors have not been considered sufficiently. Scenario-centric designs are ideal ways to improve usability. However, such designs possess some problems in practical use. To cope with these design issues, the concept of “interface scenarios” is proposed in to facilitate the interface design, and to help users understand the interaction process in such designs. The proposed scenario-focused development method for PUI is coupled with a practical application to show its effectiveness and usability.

Is your vision consistent? A method for checking, based on scenario concepts

Common sense tells us that the future is an essential element in any strategy. In addition, there is a good deal of literature on scenario planning, which is an important tool in considering the future in terms of strategy. However, in many organizations there is serious resistance to the development of scenarios, and they are not broadly implemented by companies. But even organizations that do not rely heavily on the development of scenarios do, in fact, construct visions to guide their strategies. But it might be asked, what happens when this vision is not consistent with the future? To address this problem, the present article proposes a method for checking the content and consistency of an organization's vision of the future, no matter how it was conceived. The proposed method is grounded on theoretical concepts from the field of future studies, which are described in this article. This study was motivated by the search for developing new ways of improving and using scenario techniques as a method for making strategic decisions. The method was then tested on a company in the field of information technology in order to check its operational feasibility. The test showed that the proposed method is, in fact, operationally feasible and was capable of analyzing the vision of the company being studied, indicating both its shortcomings and points of inconsistency. (C) 2007 Elsevier Ltd. All rights reserved.

A study of a soft computing based method for 3D scenario reconstruction

Several recent works deal with 3D data in mobile robotic problems, e.g., mapping. Data comes from any kind of sensor (time of flight, Kinect or 3D lasers) that provide a huge amount of unorganized 3D data. In this paper we detail an efficient approach to build complete 3D models using a soft computing method, the Growing Neural Gas (GNG). As neural models deal easily with noise, imprecision, uncertainty or partial data, GNG provides better results than other approaches. The GNG obtained is then applied to a sequence. We present a comprehensive study on GNG parameters to ensure the best result at the lowest time cost. From this GNG structure, we propose to calculate planar patches and thus obtaining a fast method to compute the movement performed by a mobile robot by means of a 3D models registration algorithm. Final results of 3D mapping are also shown.

Development priority zoning (DPZ)-led scenario simulation for regional land use change : the case of Suichang County, China

China has experienced an extraordinary level of economic development since the 1990s, following excessive competition between different regions. This has resulted in many resource and environmental problems. Land resources, for example, are either abused or wasted in many regions. The strategy of development priority zoning (DPZ), proposed by the Chinese National 11th Five-Year Plan, provides an opportunity to solve these problems by coordinating regional development and protection. In line with the rational utilization of land, it is proposed that the DPZ strategy should be integrated with regional land use policy. As there has been little research to date on this issue, this paper introduces a system dynamic (SD) model for assessing land use change in China led by the DPZ strategy. Land use is characterized by the prioritization of land development, land utilization, land harness and land protection (D-U-H-P). By using the Delphi method, a corresponding suitable prioritization of D-U-H-P for the four types of DPZ, including optimized development zones (ODZ), key development zones (KDZ), restricted development zones (RDZ), and forbidden development zones (FDZ) are identified. Suichang County is used as a case study in which to conduct the simulation of land use change under the RDZ strategy. The findings enable a conceptualization to be made of DPZ-led land use change and the identification of further implications for land use planning generally. The SD model also provides a potential tool for local government to combine DPZ strategy at the national level with land use planning at the local level.

RCA method for fault diagnosis in digital substations of power systems

The authors present a Cause-Effect fault diagnosis model, which utilises the Root Cause Analysis approach and takes into account the technical features of a digital substation. The Dempster/Shafer evidence theory is used to integrate different types of fault information in the diagnosis model so as to implement a hierarchical, systematic and comprehensive diagnosis based on the logic relationship between the parent and child nodes such as transformer/circuit-breaker/transmission-line, and between the root and child causes. A real fault scenario is investigated in the case study to demonstrate the developed approach in diagnosing malfunction of protective relays and/or circuit breakers, miss or false alarms, and other commonly encountered faults at a modern digital substation.

Rule-based transit signal priority control method using a real-time transit travel time prediction model

An advanced rule-based Transit Signal Priority (TSP) control method is presented in this paper. An on-line transit travel time prediction model is the key component of the proposed method, which enables the selection of the most appropriate TSP plans for the prevailing traffic and transit condition. The new method also adopts a priority plan re-development feature that enables modifying or even switching the already implemented priority plan to accommodate changes in the traffic conditions. The proposed method utilizes conventional green extension and red truncation strategies and also two new strategies including green truncation and queue clearance. The new method is evaluated against a typical active TSP strategy and also the base case scenario assuming no TSP control in microsimulation. The evaluation results indicate that the proposed method can produce significant benefits in reducing the bus delay time and improving the service regularity with negligible adverse impacts on the non-transit street traffic.

An improved modal strain energy method for structural damage detection, 2D simulation

Structural damage detection using modal strain energy (MSE) is one of the most efficient and reliable structural health monitoring techniques. However, some of the existing MSE methods have been validated for special types of structures such as beams or steel truss bridges which demands improving the available methods. The purpose of this study is to improve an efficient modal strain energy method to detect and quantify the damage in complex structures at early stage of formation. In this paper, a modal strain energy method was mathematically developed and then numerically applied to a fixed-end beam and a three-story frame including single and multiple damage scenarios in absence and presence of up to five per cent noise. For each damage scenario, all mode shapes and natural frequencies of intact structures and the first five mode shapes of assumed damaged structures were obtained using STRAND7. The derived mode shapes of each intact and damaged structure at any damage scenario were then separately used in the improved formulation using MATLAB to detect the location and quantify the severity of damage as compared to those obtained from previous method. It was found that the improved method is more accurate, efficient and convergent than its predecessors. The outcomes of this study can be safely and inexpensively used for structural health monitoring to minimize the loss of lives and property by identifying the unforeseen structural damages.

Scientists in Control: a progressive approach to preparing work ready graduates in QC, EQA and method evaluation

Introduction QC, EQA and method evaluation are integral to delivery of quality patient results. To ensure QUT graduates have a solid grounding in these key areas of practice, a theory-to-practice approach is used to progressively develop and consolidate these skills. Methods Using a BCG assay for serum albumin, each student undertakes an eight week project analysing two levels of QC alongside ‘patient’ samples. Results are assessed using both single rules and Multirules. Concomitantly with the QC analyses, an EQA project is undertaken; students analyse two EQA samples, twice in the semester. Results are submitted using cloud software and data for the full ‘peer group’ returned to students in spreadsheets and incomplete Youden plots. Youden plots are completed with target values and calculated ALP values and analysed for ‘lab’ and method performance. The method has a low-level positive bias, which leads to the need to investigate an alternative method. Building directly on the EQA of the first project and using the scenario of a lab that services renal patients, students undertake a method validation comparing BCP and BCG assays in another eight-week project. Precision and patient comparison studies allow students to assess whether the BCP method addresses the proportional bias of the BCG method and overall is a ‘better’ alternative method for analysing serum albumin, accounting for pragmatic factors, such as cost, as well as performance characteristics. Results Students develop understanding of the purpose and importance of QC and EQA in delivering quality results, the need to optimise testing to deliver quality results and importantly, a working knowledge of the analyses that go into ensuring this quality. In parallel to developing these key workplace competencies, students become confident, competent practitioners, able to pipette accurately and precisely and organise themselves in a busy, time pressured work environment.

Assessing clinical reasoning: A method to monitor its development in a PBL curriculum

The aim of this study was to develop and trial a method to monitor the evolution of clinical reasoning in a PBL curriculum that is suitable for use in a large medical school. Termed Clinical Reasoning Problems (CRPs), it is based on the notion that clinical reasoning is dependent on the identification and correct interpretation of certain critical clinical features. Each problem consists of a clinical scenario comprising presentation, history and physical examination. Based on this information, subjects are asked to nominate the two most likely diagnoses and to list the clinical features that they considered in formulating their diagnoses, indicating whether these features supported or opposed the nominated diagnoses. Students at different levels of medical training completed a set of 10 CRPs as well as the Diagnostic Thinking Inventory, a self-reporting questionnaire designed to assess reasoning style. Responses were scored against those of a reference group of general practitioners. Results indicate that the CRPs are an easily administered, reliable and valid assessment of clinical reasoning, able to successfully monitor its development throughout medical training. Consequently, they can be employed to assess clinical reasoning skill in individual students and to evaluate the success of undergraduate medical schools in providing effective tuition in clinical reasoning.

From environmental concerns towards sustainable food provisioning. : Material flow and food consumption scenario studies on sustainability of agri-food systems

Agriculture is an economic activity that heavily relies on the availability of natural resources. Through its role in food production agriculture is a major factor affecting public welfare and health, and its indirect contribution to gross domestic product and employment is significant. Agriculture also contributes to numerous ecosystem services through management of rural areas. However, the environmental impact of agriculture is considerable and reaches far beyond the agroecosystems. The questions related to farming for food production are, thus, manifold and of great public concern. Improving environmental performance of agriculture and sustainability of food production, sustainabilizing food production, calls for application of wide range of expertise knowledge. This study falls within the field of agro-ecology, with interphases to food systems and sustainability research and exploits the methods typical of industrial ecology. The research in these fields extends from multidisciplinary to interdisciplinary and transdisciplinary, a holistic approach being the key tenet. The methods of industrial ecology have been applied extensively to explore the interaction between human economic activity and resource use. Specifically, the material flow approach (MFA) has established its position through application of systematic environmental and economic accounting statistics. However, very few studies have applied MFA specifically to agriculture. The MFA approach was used in this thesis in such a context in Finland. The focus of this study is the ecological sustainability of primary production. The aim was to explore the possibilities of assessing ecological sustainability of agriculture by using two different approaches. In the first approach the MFA-methods from industrial ecology were applied to agriculture, whereas the other is based on the food consumption scenarios. The two approaches were used in order to capture some of the impacts of dietary changes and of changes in production mode on the environment. The methods were applied at levels ranging from national to sector and local levels. Through the supply-demand approach, the viewpoint changed between that of food production to that of food consumption. The main data sources were official statistics complemented with published research results and expertise appraisals. MFA approach was used to define the system boundaries, to quantify the material flows and to construct eco-efficiency indicators for agriculture. The results were further elaborated for an input-output model that was used to analyse the food flux in Finland and to determine its relationship to the economy-wide physical and monetary flows. The methods based on food consumption scenarios were applied at regional and local level for assessing feasibility and environmental impacts of relocalising food production. The approach was also used for quantification and source allocation of greenhouse gas (GHG) emissions of primary production. GHG assessment provided, thus, a means of crosschecking the results obtained by using the two different approaches. MFA data as such or expressed as eco-efficiency indicators, are useful in describing the overall development. However, the data are not sufficiently detailed for identifying the hot spots of environmental sustainability. Eco-efficiency indicators should not be bluntly used in environmental assessment: the carrying capacity of the nature, the potential exhaustion of non-renewable natural resources and the possible rebound effect need also to be accounted for when striving towards improved eco-efficiency. The input-output model is suitable for nationwide economy analyses and it shows the distribution of monetary and material flows among the various sectors. Environmental impact can be captured only at a very general level in terms of total material requirement, gaseous emissions, energy consumption and agricultural land use. Improving environmental performance of food production requires more detailed and more local information. The approach based on food consumption scenarios can be applied at regional or local scales. Based on various diet options the method accounts for the feasibility of re-localising food production and environmental impacts of such re-localisation in terms of nutrient balances, gaseous emissions, agricultural energy consumption, agricultural land use and diversity of crop cultivation. The approach is applicable anywhere, but the calculation parameters need to be adjusted so as to comply with the specific circumstances. The food consumption scenario approach, thus, pays attention to the variability of production circumstances, and may provide some environmental information that is locally relevant. The approaches based on the input-output model and on food consumption scenarios represent small steps towards more holistic systemic thinking. However, neither one alone nor the two together provide sufficient information for sustainabilizing food production. Environmental performance of food production should be assessed together with the other criteria of sustainable food provisioning. This requires evaluation and integration of research results from many different disciplines in the context of a specified geographic area. Foodshed area that comprises both the rural hinterlands of food production and the population centres of food consumption is suggested to represent a suitable areal extent for such research. Finding a balance between the various aspects of sustainability is a matter of optimal trade-off. The balance cannot be universally determined, but the assessment methods and the actual measures depend on what the bottlenecks of sustainability are in the area concerned. These have to be agreed upon among the actors of the area

Volatility Smile Dynamics in Scenario Analysis

The objective of this paper is to suggest a method that accounts for the impact of the volatility smile dynamics when performing scenario analysis for a portfolio consisting of vanilla options. As the volatility smile is documented to change at least with the level of implied at-the-money volatility, a suitable model is here included in the calculation process of the simulated market scenarios. By constructing simple portfolios of index options and comparing the ex ante risk exposure measured using different pricing methods to realized market values, ex post, the improvements of the incorporation of the model are monitored. The analyzed examples in the study generate results that statistically support that the most accurate scenarios are those calculated using the model accounting for the dynamics of the smile. Thus, we show that the differences emanating from the volatility smile are apparent and should be accounted for and that the methodology presented herein is one suitable alternative for doing so.

Numerical simulation of axisymmetric unsteady incompressible flow by a vorticity-velocity method

A new numerical method for solving the axisymmetric unsteady incompressible Navier-Stokes equations using vorticity-velocity variables and a staggered grid is presented. The solution is advanced in time with an explicit two-stage Runge-Kutta method. At each stage a vector Poisson equation for velocity is solved. Some important aspects of staggering of the variable location, divergence-free correction to the velocity held by means of a suitably chosen scalar potential and numerical treatment of the vorticity boundary condition are examined. The axisymmetric spherical Couette flow between two concentric differentially rotating spheres is computed as an initial value problem. Comparison of the computational results using a staggered grid with those using a non-staggered grid shows that the staggered grid is superior to the non-staggered grid. The computed scenario of the transition from zero-vortex to two-vortex flow at moderate Reynolds number agrees with that simulated using a pseudospectral method, thus validating the temporal accuracy of our method.

Scenario Cluster Lagrangian Decomposition in two stage stochastic mixed 0-1 optimization

In this paper we introduce four scenario Cluster based Lagrangian Decomposition (CLD) procedures for obtaining strong lower bounds to the (optimal) solution value of two-stage stochastic mixed 0-1 problems. At each iteration of the Lagrangian based procedures, the traditional aim consists of obtaining the solution value of the corresponding Lagrangian dual via solving scenario submodels once the nonanticipativity constraints have been dualized. Instead of considering a splitting variable representation over the set of scenarios, we propose to decompose the model into a set of scenario clusters. We compare the computational performance of the four Lagrange multiplier updating procedures, namely the Subgradient Method, the Volume Algorithm, the Progressive Hedging Algorithm and the Dynamic Constrained Cutting Plane scheme for different numbers of scenario clusters and different dimensions of the original problem. Our computational experience shows that the CLD bound and its computational effort depend on the number of scenario clusters to consider. In any case, our results show that the CLD procedures outperform the traditional LD scheme for single scenarios both in the quality of the bounds and computational effort. All the procedures have been implemented in a C++ experimental code. A broad computational experience is reported on a test of randomly generated instances by using the MIP solvers COIN-OR and CPLEX for the auxiliary mixed 0-1 cluster submodels, this last solver within the open source engine COIN-OR. We also give computational evidence of the model tightening effect that the preprocessing techniques, cut generation and appending and parallel computing tools have in stochastic integer optimization. Finally, we have observed that the plain use of both solvers does not provide the optimal solution of the instances included in the testbed with which we have experimented but for two toy instances in affordable elapsed time. On the other hand the proposed procedures provide strong lower bounds (or the same solution value) in a considerably shorter elapsed time for the quasi-optimal solution obtained by other means for the original stochastic problem.