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Policymakers need to make policies for an uncertain future, and policy analysts assist policymakers in choosing preferred courses of action. Despite a longstanding recognition that the futures field can contribute a great deal to policy analysis, futures work is not used to its full potential as an element of policy analysis. This is partly due to an absence of well-defined links between the fields and a common unambiguous typology. This paper proposes a framework for linking policy analysis, policymaking, and the futures field so that they can benefit mutually from a shared approach and tools. This integrated framework is intended to guide policy analysts on the appropriate use of futures approaches so that they can improve their analyses and contribute to better policies. At the same time, futures practitioners will be encouraged to align their approaches with the needs of policy analysts, thereby leading to increased uptake of futures work in policy analysis.
Cornelis van Dorsser; Poonam Taneja; Warren Walker; Vincent Marchau. An integrated framework for anticipating the future and dealing with uncertainty in policymaking. Futures 2020, 124, 102594 .
AMA StyleCornelis van Dorsser, Poonam Taneja, Warren Walker, Vincent Marchau. An integrated framework for anticipating the future and dealing with uncertainty in policymaking. Futures. 2020; 124 ():102594.
Chicago/Turabian StyleCornelis van Dorsser; Poonam Taneja; Warren Walker; Vincent Marchau. 2020. "An integrated framework for anticipating the future and dealing with uncertainty in policymaking." Futures 124, no. : 102594.
DAP is a DMDU approach for designing a plan that explicitly includes provisions for adaptation as conditions change and knowledge is gained. The resulting plan combines actions to be taken right away with those that make important commitments to shape the future and those that preserve needed flexibility for the future. The approach includes the specification of a monitoring system, together with the specification of actions to be taken when specific trigger values are reached. This chapter describes the DAP approach and illustrates it with a (more or less) fictitious case. A real-life application is given in Chap. 8.
Warren E. Walker; Vincent A. W. J. Marchau; Jan H. Kwakkel. Dynamic Adaptive Planning (DAP). Decision Making under Deep Uncertainty 2019, 53 -69.
AMA StyleWarren E. Walker, Vincent A. W. J. Marchau, Jan H. Kwakkel. Dynamic Adaptive Planning (DAP). Decision Making under Deep Uncertainty. 2019; ():53-69.
Chicago/Turabian StyleWarren E. Walker; Vincent A. W. J. Marchau; Jan H. Kwakkel. 2019. "Dynamic Adaptive Planning (DAP)." Decision Making under Deep Uncertainty , no. : 53-69.
Policymakers need to make policies for unknown and uncertain futures. Researchers in the futures field have a great deal to contribute to the policymaking process. But, futures research is often neglected as an element of policymaking. The aim of this paper is to improve the link between futures research and policymaking. More specifically, as Policy Analysis has a strong link with policymaking, this paper explores the possibility of linking Policy Analysis to the futures field through the use of an uncertainty typology applied in Policy Analysis. The typology can be used to structure the various forward-looking disciplines (or subfields) of the futures field according to the level of uncertainty that they address. This linkage can add significantly to the use of futures research in policymaking.
Cornelis van Dorsser; Warren E. Walker; Poonam Taneja; Vincent A.W.J. Marchau. Improving the link between the futures field and policymaking. Futures 2018, 104, 75 -84.
AMA StyleCornelis van Dorsser, Warren E. Walker, Poonam Taneja, Vincent A.W.J. Marchau. Improving the link between the futures field and policymaking. Futures. 2018; 104 ():75-84.
Chicago/Turabian StyleCornelis van Dorsser; Warren E. Walker; Poonam Taneja; Vincent A.W.J. Marchau. 2018. "Improving the link between the futures field and policymaking." Futures 104, no. : 75-84.
Here we examine whether a study conducted 25 years ago (1992) would have had different conclusions if concepts and analytical methods developed since then had been used. The 1992 problem was to identify a strategy for reducing flood risk in the Netherlands by, for example, strengthening the river dikes against the risk of flooding. Since then, conditions related to flooding have been recognised as increasingly uncertain. In response, a new paradigm for strategic planning has emerged: the ‘adaptive planning approach’, which aims to identify and assess strategies allowing for change, learning, and adaptation over time. We found that using the adaptive planning approach in 1992 would not have changed the main conclusions. But, it would have made explicit the need for the identification of vulnerabilities of the chosen strategy, a monitoring system to keep track of the uncertainties, and the possible actions to deal with the vulnerabilities that can be taken as the world evolves.
Matthijs Kok; Odette Van De Riet; Warren E. Walker. Back to the future: Viewing a 1992 flood risk study through a 2017 lens. Journal of Flood Risk Management 2018, 12, e12456 .
AMA StyleMatthijs Kok, Odette Van De Riet, Warren E. Walker. Back to the future: Viewing a 1992 flood risk study through a 2017 lens. Journal of Flood Risk Management. 2018; 12 (1):e12456.
Chicago/Turabian StyleMatthijs Kok; Odette Van De Riet; Warren E. Walker. 2018. "Back to the future: Viewing a 1992 flood risk study through a 2017 lens." Journal of Flood Risk Management 12, no. 1: e12456.
Glynn et al. (2017) note the importance of engaging stakeholders in the process of public policymaking and analysis. In particular, they highlight the central role biases, beliefs, heuristics, and values (BBVH) play in such engagement. However, the framework they propose neglects uncertainty, which significantly restricts any ability to engage effectively with BBHV. We show how their paper's narrow view can be widened to include aspects of risk and uncertainty.
Warren Walker; Vincent Marchau; Pieter Bloemen; Judy Lawrence; Robert Lempert; Jan Kwakkel. Comment on “From Data to Decisions: Processing Information, Biases, and Beliefs for Improved Management of Natural Resources and Environments” by Glynn et al. Earth's Future 2018, 6, 757 -761.
AMA StyleWarren Walker, Vincent Marchau, Pieter Bloemen, Judy Lawrence, Robert Lempert, Jan Kwakkel. Comment on “From Data to Decisions: Processing Information, Biases, and Beliefs for Improved Management of Natural Resources and Environments” by Glynn et al. Earth's Future. 2018; 6 (5):757-761.
Chicago/Turabian StyleWarren Walker; Vincent Marchau; Pieter Bloemen; Judy Lawrence; Robert Lempert; Jan Kwakkel. 2018. "Comment on “From Data to Decisions: Processing Information, Biases, and Beliefs for Improved Management of Natural Resources and Environments” by Glynn et al." Earth's Future 6, no. 5: 757-761.
By 2050, about two-thirds of the world’s people are expected to live in urban areas. But, the economic viability and sustainability of city centers is threatened by problems related to transport, such as pollution, congestion, and parking. Much has been written about automated vehicles and demand responsive transport. The combination of these potentially disruptive developments could reduce these problems. However, implementation is held back by uncertainties, including public acceptance, liability, and privacy. So, their potential to reduce urban transport problems may not be fully realized. We propose an adaptive approach to implementation that takes some actions right away and creates a framework for future actions that allows for adaptations over time as knowledge about performance and acceptance of the new system (called ‘automated taxis’) accumulates and critical events for implementation take place. The adaptive approach is illustrated in the context of a hypothetical large city
Warren E. Walker; Vincent A.W.J. Marchau. Dynamic adaptive policymaking for the sustainable city: The case of automated taxis. International Journal of Transportation Science and Technology 2017, 6, 1 -12.
AMA StyleWarren E. Walker, Vincent A.W.J. Marchau. Dynamic adaptive policymaking for the sustainable city: The case of automated taxis. International Journal of Transportation Science and Technology. 2017; 6 (1):1-12.
Chicago/Turabian StyleWarren E. Walker; Vincent A.W.J. Marchau. 2017. "Dynamic adaptive policymaking for the sustainable city: The case of automated taxis." International Journal of Transportation Science and Technology 6, no. 1: 1-12.
A variety of model-based approaches for supporting decision-making under deep uncertainty have been suggested, but they are rarely compared and contrasted. In this paper, we compare Robust Decision-Making with Dynamic Adaptive Policy Pathways. We apply both to a hypothetical case inspired by a river reach in the Rhine Delta of the Netherlands, and compare them with respect to the required tooling, the resulting decision relevant insights, and the resulting plans. The results indicate that the two approaches are complementary. Robust Decision-Making offers insights into conditions under which problems occur, and makes trade-offs transparent. The Dynamic Adaptive Policy Pathways approach emphasizes dynamic adaptation over time, and thus offers a natural way for handling the vulnerabilities identified through Robust Decision-Making. The application also makes clear that the analytical process of Robust Decision-Making is path-dependent and open ended: an analyst has to make many choices, for which Robust Decision-Making offers no direct guidance. This paper compares Robust Decision-Making (RDM) and Dynamic Adaptive Policy Pathways (DAPP).RDM and DAPP have different merits, which highlight their complementarity.RDM has a clear analytical process and the application is reasonably straight forward.DAPP offers a convenient framework for designing plans for dynamic adaptation over time.
Jan H. Kwakkel; Marjolijn Haasnoot; Warren E. Walker. Comparing Robust Decision-Making and Dynamic Adaptive Policy Pathways for model-based decision support under deep uncertainty. Environmental Modelling & Software 2016, 86, 168 -183.
AMA StyleJan H. Kwakkel, Marjolijn Haasnoot, Warren E. Walker. Comparing Robust Decision-Making and Dynamic Adaptive Policy Pathways for model-based decision support under deep uncertainty. Environmental Modelling & Software. 2016; 86 ():168-183.
Chicago/Turabian StyleJan H. Kwakkel; Marjolijn Haasnoot; Warren E. Walker. 2016. "Comparing Robust Decision-Making and Dynamic Adaptive Policy Pathways for model-based decision support under deep uncertainty." Environmental Modelling & Software 86, no. : 168-183.
Jan H. Kwakkel; Warren E. Walker; Marjolijn Haasnoot. Coping with the Wickedness of Public Policy Problems: Approaches for Decision Making under Deep Uncertainty. Journal of Water Resources Planning and Management 2016, 142, 01816001 .
AMA StyleJan H. Kwakkel, Warren E. Walker, Marjolijn Haasnoot. Coping with the Wickedness of Public Policy Problems: Approaches for Decision Making under Deep Uncertainty. Journal of Water Resources Planning and Management. 2016; 142 (3):01816001.
Chicago/Turabian StyleJan H. Kwakkel; Warren E. Walker; Marjolijn Haasnoot. 2016. "Coping with the Wickedness of Public Policy Problems: Approaches for Decision Making under Deep Uncertainty." Journal of Water Resources Planning and Management 142, no. 3: 01816001.
Megaprojects are large, costly, complex infrastructure projects. To assess the financial viability of a megaproject, a cost—benefit analysis (CBA) is usually performed; the results depend upon the accuracy of the cost estimations and the predictive models used to forecast future demand for the use of the infrastructure. The outcomes of the models are very vulnerable to unexpected events. As a result, the CBA may become unreliable and give an unrealistic picture of the financial viability of a project. An alternative way of policy making that tries to take uncertainty into account is the dynamic adaptive policy (DAP) approach. This approach involves a systematic method for designing and implementing a policy over time that is based on a clear set of constraints and objectives and that involves monitoring the environment, gathering information, and adjusting and readjusting to new circumstances. The efficacy of this type of policy making has already been shown, but whether DAP leads to a better cost—benefit performance of megaprojects is unknown. In this paper we focus on answering two research questions: How can CBA be applied to DAP? How good is the cost—benefit performance of megaprojects when using DAP compared with the cost—benefit performance when using the static policy-making approach? In this paper a framework based on real options theory is specified, enabling a CBA to be performed on a dynamic adaptive policy. This framework is then applied to a case involving Schiphol Airport, Amsterdam, to compare the cost—benefit performance of the static policy with the cost—benefit performance using the DAP approach. For this case, the cost—benefit performance of the megaproject under the DAP approach turns out to be better compared with its performance under the static policy. This result provides a first indication that adaptive policies might be able to improve the cost—benefit performance of megaprojects.
Jerrel R Yzer; Warren E Walker; Vincent A W J Marchau; Jan H Kwakkel. Dynamic Adaptive Policies: A Way to Improve the Cost—Benefit Performance of Megaprojects? Environment and Planning B: Planning and Design 2014, 41, 594 -612.
AMA StyleJerrel R Yzer, Warren E Walker, Vincent A W J Marchau, Jan H Kwakkel. Dynamic Adaptive Policies: A Way to Improve the Cost—Benefit Performance of Megaprojects? Environment and Planning B: Planning and Design. 2014; 41 (4):594-612.
Chicago/Turabian StyleJerrel R Yzer; Warren E Walker; Vincent A W J Marchau; Jan H Kwakkel. 2014. "Dynamic Adaptive Policies: A Way to Improve the Cost—Benefit Performance of Megaprojects?" Environment and Planning B: Planning and Design 41, no. 4: 594-612.
A new paradigm for planning under conditions of deep uncertainty has emerged in the literature. According to this paradigm, a planner should create a strategic vision of the future, commit to short-term actions, and establish a framework to guide future actions. A plan that embodies these ideas allows for its dynamic adaptation over time to meet changing circumstances. We propose a method for decisionmaking under uncertain global and regional changes called ‘Dynamic Adaptive Policy Pathways’. We base our approach on two complementary approaches for designing adaptive plans: ‘Adaptive Policymaking’ and ‘Adaptation Pathways’. Adaptive Policymaking is a theoretical approach describing a planning process with different types of actions (e.g. ‘mitigating actions’ and ‘hedging actions’) and signposts to monitor to see if adaptation is needed. In contrast, Adaptation Pathways provides an analytical approach for exploring and sequencing a set of possible actions based on alternative external developments over time. We illustrate the Dynamic Adaptive Policy Pathways approach by producing an adaptive plan for long-term water management of the Rhine Delta in the Netherlands that takes into account the deep uncertainties about the future arising from social, political, technological, economic, and climate changes. The results suggest that it is worthwhile to further test and use the approach
Marjolijn Haasnoot; Jan H. Kwakkel; Warren E. Walker; Judith ter Maat. Dynamic adaptive policy pathways: A method for crafting robust decisions for a deeply uncertain world. Global Environmental Change 2013, 23, 485 -498.
AMA StyleMarjolijn Haasnoot, Jan H. Kwakkel, Warren E. Walker, Judith ter Maat. Dynamic adaptive policy pathways: A method for crafting robust decisions for a deeply uncertain world. Global Environmental Change. 2013; 23 (2):485-498.
Chicago/Turabian StyleMarjolijn Haasnoot; Jan H. Kwakkel; Warren E. Walker; Judith ter Maat. 2013. "Dynamic adaptive policy pathways: A method for crafting robust decisions for a deeply uncertain world." Global Environmental Change 23, no. 2: 485-498.
There is increasing interest in long-term plans that can adapt to changing situations under conditions of deep uncertainty. We argue that a sustainable plan should not only achieve economic, environmental, and social objectives, but should be robust and able to be adapted over time to (unforeseen) future conditions. Large numbers of papers dealing with robustness and adaptive plans have begun to appear, but the literature is fragmented. The papers appear in disparate journals, and deal with a wide variety of policy domains. This paper (1) describes and compares a family of related conceptual approaches to designing a sustainable plan, and (2) describes several computational tools supporting these approaches. The conceptual approaches all have their roots in an approach to long-term planning called Assumption-Based Planning. Guiding principles for the design of a sustainable adaptive plan are: explore a wide variety of relevant uncertainties, connect short-term targets to long-term goals over time, commit to short-term actions while keeping options open, and continuously monitor the world and take actions if necessary. A key computational tool across the conceptual approaches is a fast, simple (policy analysis) model that is used to make large numbers of runs, in order to explore the full range of uncertainties and to identify situations in which the plan would fail.
Warren E. Walker; Marjolijn Haasnoot; Jan H. Kwakkel. Adapt or Perish: A Review of Planning Approaches for Adaptation under Deep Uncertainty. Sustainability 2013, 5, 955 -979.
AMA StyleWarren E. Walker, Marjolijn Haasnoot, Jan H. Kwakkel. Adapt or Perish: A Review of Planning Approaches for Adaptation under Deep Uncertainty. Sustainability. 2013; 5 (3):955-979.
Chicago/Turabian StyleWarren E. Walker; Marjolijn Haasnoot; Jan H. Kwakkel. 2013. "Adapt or Perish: A Review of Planning Approaches for Adaptation under Deep Uncertainty." Sustainability 5, no. 3: 955-979.
Exploratory Modeling and Analysis (EMA) is a research methodology that uses computational experiments to analyze complex and uncertain systems (Bankes 1993, 1994). EMA can be understood as searching or sampling over an ensemble of models that are plausible given a priori knowledge, or are otherwise of interest. This ensemble may often be large or infinite in size. Consequently, the central challenge of exploratory modeling is the design of search or sampling strategies that support valid conclusions or reliable insights based on a limited number of computational experiments. EMA can be contrasted with the use of models to predict system behavior, where models are built by consolidating known facts into a single package (Hodges 1991). When experimentally validated, this single model can be used for analysis as a surrogate for the actual system. Examples of this approach include the engineering models that are used in computer-aided design systems. Where applicable
Steve Bankes; Warren E. Walker; Jan H. Kwakkel. Exploratory Modeling and Analysis. Encyclopedia of Operations Research and Management Science 2013, 532 -537.
AMA StyleSteve Bankes, Warren E. Walker, Jan H. Kwakkel. Exploratory Modeling and Analysis. Encyclopedia of Operations Research and Management Science. 2013; ():532-537.
Chicago/Turabian StyleSteve Bankes; Warren E. Walker; Jan H. Kwakkel. 2013. "Exploratory Modeling and Analysis." Encyclopedia of Operations Research and Management Science , no. : 532-537.
Synonyms: uncertainty, doubt, dubiety, skepticism, suspicion, mistrust, mean lack of sureness about someone or something. Uncertainty may range from falling short of certainty to an almost complete lack of conviction or knowledge especially about an outcome or result. Doubt suggests both uncertainty and inability to make a decision. Dubiety stresses a wavering between conclusions. Skepticism implies unwillingness to believe without conclusive evidence. Suspicion stresses lack of faith in the truth, reality, fairness, or reliability of something or someone. Mistrust implies a genuine doubt based upon suspicion. [Merriam-Webster Online Dictionary].
Warren E. Walker; Vincent A. W. J. Marchau; Jan Kwakkel. Uncertainty in the Framework of Policy Analysis. Handbook of Healthcare Logistics 2012, 215 -261.
AMA StyleWarren E. Walker, Vincent A. W. J. Marchau, Jan Kwakkel. Uncertainty in the Framework of Policy Analysis. Handbook of Healthcare Logistics. 2012; ():215-261.
Chicago/Turabian StyleWarren E. Walker; Vincent A. W. J. Marchau; Jan Kwakkel. 2012. "Uncertainty in the Framework of Policy Analysis." Handbook of Healthcare Logistics , no. : 215-261.
The world is undergoing rapid changes. The future is uncertain. Policymakers are faced with problem situations that are complex, and with alternative courses of action that can produce far-reaching consequences that are hard to predict. Different groups perceive and value the problem situation and the alternative actions differently. Nevertheless, policymakers have a responsibility to develop and implement policies that have the best chance of contributing to the health, safety, and well being of their constituencies. Given this context, policymaking is not easy. Uncertainties abound. Data are limited. Identifying the key issues is a difficult task. However, without proper analysis and guidance, important policy choices end up being based on hunches and guesses, and policy processes may get stuck for long periods—sometimes with regrettable results.
Wil A. H. Thissen; Warren E. Walker. Introduction. Handbook of Healthcare Logistics 2012, 179, 1 -8.
AMA StyleWil A. H. Thissen, Warren E. Walker. Introduction. Handbook of Healthcare Logistics. 2012; 179 ():1-8.
Chicago/Turabian StyleWil A. H. Thissen; Warren E. Walker. 2012. "Introduction." Handbook of Healthcare Logistics 179, no. : 1-8.
Although quantitative system models are only one of many tools of a policy analyst, they are an important tool. For the policy analyst, the purpose of building and using models is to estimate things that cannot be observed or measured directly. The prime example is impact assessment—estimating the outcomes of a policy that a decisionmaker may consider adopting. Other uses are diagnosis (estimating what factors have the greatest leverage to change a specified outcome or what is the primary source of a given outcome) and forecasting (estimating how a variable is likely to evolve in the future, usually assuming “present trends”). They also may be used as learning tools (to gain an understanding of how the system works, or may work in the future).
Warren E. Walker; C. Els Van Daalen. System Models for Policy Analysis. International Series in Operations Research & Management Science 2012, 179, 157 -184.
AMA StyleWarren E. Walker, C. Els Van Daalen. System Models for Policy Analysis. International Series in Operations Research & Management Science. 2012; 179 ():157-184.
Chicago/Turabian StyleWarren E. Walker; C. Els Van Daalen. 2012. "System Models for Policy Analysis." International Series in Operations Research & Management Science 179, no. : 157-184.
In this paper we assess the efficacy of a dynamic adaptive planning (DAP) approach for guiding the long-term development of infrastructure. The efficacy of the approach is tested on the specific case of airport strategic planning. Utilizing a fast and simple model of an airport, and a composition of small models that can generate a wide spectrum of alternative futures, the performance of a dynamic adaptive plan is compared with the performance of a static, rigid implementation plan across a wide spectrum of conceivable futures. These computational experiments reveal that the static rigid plan outperforms the dynamic adaptive plan in only a small part of the spectrum. Moreover, given the wide array of possible futures, the dynamic adaptive plan has a narrower spread of outcomes than the static rigid plan, implying that the dynamic adaptive plan exposes planners to less uncertainty about its future performance despite the wide variety of uncertainties that are present. These computational results confirm theoretical hypotheses in the literature that DAP approaches are more efficacious for planning under uncertainty.
Jan H Kwakkel; Warren E Walker; Vincent A W J Marchau. Assessing the Efficacy of Dynamic Adaptive Planning of Infrastructure: Results from Computational Experiments. Environment and Planning B: Planning and Design 2012, 39, 533 -550.
AMA StyleJan H Kwakkel, Warren E Walker, Vincent A W J Marchau. Assessing the Efficacy of Dynamic Adaptive Planning of Infrastructure: Results from Computational Experiments. Environment and Planning B: Planning and Design. 2012; 39 (3):533-550.
Chicago/Turabian StyleJan H Kwakkel; Warren E Walker; Vincent A W J Marchau. 2012. "Assessing the Efficacy of Dynamic Adaptive Planning of Infrastructure: Results from Computational Experiments." Environment and Planning B: Planning and Design 39, no. 3: 533-550.
Flexibility is a term used in various fields with widely differing interpretations. Moreover, several related concepts, such as adaptability, exist that have an overlap in meaning or are simply used synonymously. This article presents a framing of flexibility, and three concepts with which it bears a close family resemblance, for the use in the context of infrastructure constellations. The definitions proposed in this frame draw inspiration from existing literature, though they are not based upon a classical literature review. Rather, a usable set of definitions is proposed for the intended context. The definitions all have the same structure to better appreciate how the concepts are related and how they differ. To verify whether the definitions correspond to their practical use, a data-mining exercise is performed on over 11,000 scientific articles that use the concepts of flexibility. After the corpus of articles is identified that is close to the intended field of application (infrastructure constellations), a co-occurrence analysis is carried out in order to clarify the differences between the concepts and to give nuance to the meaning conveyed in the definitions.
J. De Haan; J.H. Kwakkel; W.E. Walker; J. Spirco; W.A.H. Thissen. Framing flexibility: Theorising and data mining to develop a useful definition of flexibility and related concepts. Futures 2011, 43, 923 -933.
AMA StyleJ. De Haan, J.H. Kwakkel, W.E. Walker, J. Spirco, W.A.H. Thissen. Framing flexibility: Theorising and data mining to develop a useful definition of flexibility and related concepts. Futures. 2011; 43 (9):923-933.
Chicago/Turabian StyleJ. De Haan; J.H. Kwakkel; W.E. Walker; J. Spirco; W.A.H. Thissen. 2011. "Framing flexibility: Theorising and data mining to develop a useful definition of flexibility and related concepts." Futures 43, no. 9: 923-933.
Recent advances in computers, networking, and telecommunications offer new opportunities for using simulation and gaming as methodological tools for improving crisis management. It has become easy to develop virtual environments to support games, to have players at distributed workstations interacting with each other, to have automated controllers supply exogenous events to the players, to enable players to query online data files during the game, and to prepare presentation graphics for use during the game and for post-game debriefings. Videos can be used to present scenario updates to players in “newscast” format and to present pre-taped briefings by experts to players. Organizations responsible for crisis management are already using such technologies in constructing crisis management systems (CMSs) to coordinate response to a crisis, provide decision support during a crisis, and support activities prior to the crisis and after the crisis. If designed with gaming in mind, those same CMSs could be easily used in a simulation mode to play a crisis management game. Such a use of the system would also provide personnel with opportunities to rehearse for real crises using the same tools they would have available to them in a real crisis. In this paper, we provide some background for the use of simulation and gaming in crisis management training, describe an architecture for simulation and gaming, and present a case study to illustrate how virtual environments can be used for crisis management training.
Warren E. Walker; Jordan Giddings; Stuart Armstrong. Training and learning for crisis management using a virtual simulation/gaming environment. Cognition, Technology & Work 2011, 13, 163 -173.
AMA StyleWarren E. Walker, Jordan Giddings, Stuart Armstrong. Training and learning for crisis management using a virtual simulation/gaming environment. Cognition, Technology & Work. 2011; 13 (3):163-173.
Chicago/Turabian StyleWarren E. Walker; Jordan Giddings; Stuart Armstrong. 2011. "Training and learning for crisis management using a virtual simulation/gaming environment." Cognition, Technology & Work 13, no. 3: 163-173.
Infrastructure systems are crucial to the functioning of society. Their long-term planning is therefore of great importance. Uncertainty about the future conditions under which an infrastructure system will function is of particular importance for successful long-term planning. The uncertainties about the future encountered in the long term planning of infrastructure systems is increasing due to developments such as privatization, liberalization, globalization, and climate change. Despite the increasing uncertainty, planning is still based on the outdated assumption that the future can be predicted accurately enough for static planning. We review the state of the art of an alternative planning paradigm that starts from the explicit recognition of the inability of forecasting and the need for adaptivity and flexibility. In light of the review, we present a research agenda identifying four areas of research: the methods and techniques employed for crafting adaptive policies, the institutional challenges for the successful implementation of adaptive policies, research into the efficacy of adaptive policies, and questions related to the assessment of the costs and benefits of adaptiveness.
Jan. H. Kwakkel; Warren E. Walker. Grappling with uncertainty in the long-term development of infrastructure systems. Next generation infrastructure systems for eco-cities 2010, 1 -6.
AMA StyleJan. H. Kwakkel, Warren E. Walker. Grappling with uncertainty in the long-term development of infrastructure systems. Next generation infrastructure systems for eco-cities. 2010; ():1-6.
Chicago/Turabian StyleJan. H. Kwakkel; Warren E. Walker. 2010. "Grappling with uncertainty in the long-term development of infrastructure systems." Next generation infrastructure systems for eco-cities , no. : 1-6.
Warren E. Walker; Vincent A.W.J. Marchau; Darren Swanson. Addressing deep uncertainty using adaptive policies: Introduction to section 2. Technological Forecasting and Social Change 2010, 77, 917 -923.
AMA StyleWarren E. Walker, Vincent A.W.J. Marchau, Darren Swanson. Addressing deep uncertainty using adaptive policies: Introduction to section 2. Technological Forecasting and Social Change. 2010; 77 (6):917-923.
Chicago/Turabian StyleWarren E. Walker; Vincent A.W.J. Marchau; Darren Swanson. 2010. "Addressing deep uncertainty using adaptive policies: Introduction to section 2." Technological Forecasting and Social Change 77, no. 6: 917-923.