Testing the Scenario Hypothesis: The Effect of Alternative Characterizations of Uncertainty on Decision Structuring

目前人们对决策支持有相当大的兴趣，这可能有助于改进困难的决策，例如规划者在考虑不确定的长期环境变化时所作的决策。以往的研究和实践表明，基于场景的规划过程可以帮助决策者通过设计额外的和自适应的选项来重组决策。本研究通过比较决策支持工具的决策来验证这一假设，这些决策支持工具以两种方式之一提供预测：要么通过提供最佳估计概率，要么通过提供替代方案。假设表明，场景版本将导致决策选项成功重组的更高概率。参与者面临着管理假想渔业的挑战。他们以个人或团体的形式，在一段时期内制定适当的捕捞限制政策，直至未来。然后，参与者使用交互式渔业模型决策支持工具，帮助他们评估备选方案并设计新的备选方案，同时对可用的备选方案及其潜在性能进行合理的限制。与会者被告知，关键的输入数据，如渔业的可持续产量，是科学分歧的主题，导致对未来的严重不确定性。渔业模型将表明，与其他决策方案相比，特定的适应性管理策略将使参与者满意。在对可持续收益和其他不确定性的广泛预期中，目标相互冲突。但最初给参与者的选择并不包括这种适应性策略，他们也不会立即发现这种策略的存在。主要的实验操作是决策支持工具是根据最佳估计预测还是根据情景组织信息。主要的结果度量是确定成功的适应策略的概率。帮助决策者设计新的和可能更成功的决策选择的能力可能是决策支持的一个有价值的方面。但是，很多关于决策制定和决策支持的研究都侧重于在一组固定的选项中做出选择，而不是设计可能减少困难权衡的新选项。深层次不确定性的存在？决策者可能对偶然性和概率不确定？可能会使理解或同意备选方案的潜在后果变得更加困难，从而更有效地设计新方案。这些实验的结果揭示了复杂的、高度不确定的政策决策所涉及的社会和心理过程。这项工作还有助于改进决策支助方法，并有助于正在进行的关于传达极不确定信息的最有效手段的政策讨论。

There is considerable current interest in decision support that might help improve difficult decisions, such as those that planners make when considering uncertain, long-term environmental changes. Previous research and practice suggests that scenario-based planning processes can help decision makers to restructure decisions by designing additional and adaptive options. This research tests this scenario hypothesis by comparing decisions using decision-support tools that provide forecasts in one of two ways: either by presenting best-estimate probabilities or by presenting alternative scenarios. The hypothesis states that the scenario version will lead to higher probability of a successful restructuring of the decision options. Participants have the challenge of managing a hypothetical fishery. Acting as individuals or in groups, they set a suitable catch-limit policy for a period extending into the future. Participants then use an interactive fisheries model decision-support tool that helps them to evaluate options and to design new ones, while placing reasonable constraints on the options available and their potential performance. Participants are informed that key input data, such as the sustainable yield from the fishery, are the subject of scientific disagreement, resulting in deep uncertainty about the future. The fisheries model will show that a particular adaptive management strategy will, in contrast to other decision options, satisfy the participants? conflicting objectives over a wide range of expectations about sustainable yield and other uncertainties. But the options initially given the participants will not include this adaptive strategy nor will they find it immediately obvious that such a strategy exists. The primary experimental manipulation is whether the decision-support tool organizes information in terms of best-estimate forecasts or in terms of scenarios. The primary outcome measure is the probability of identifying the successful adaptive strategy. The ability to help decision makers design new and potentially more successful decision options could be a valued aspect of decision support. But much research on decision making and decision support focuses on choice among a fixed set of options, rather than on the design of new options that might reduce difficult tradeoffs. The presence of deep uncertainty ? where decision makers may be unsure about contingencies and probabilities ? can make it even more difficult to understand or agree on the potential consequences of alternative options, and thus to design new options effectively. The results of these experiments shed light on the social and psychological processes involved in complex, deeply-uncertain policy decisions. The work also informs improvements in decision support methodologies and contributes to ongoing policy discussions regarding the most effective means of conveying deeply uncertain information.