决策中采用复杂性科学的软肋:努力应对经常被忽视的非技术挑战

IF 3.8 3区 管理学 Q1 PUBLIC ADMINISTRATION
Darren Nel, Araz Taeihagh
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引用次数: 0

摘要

社会-技术系统的不断深化整合创造了极其复杂的环境,造成了越来越不确定和不可预测的情况。在这种情况下,人们鼓励决策者在制定政策时借鉴以复杂性科学为依据的方法,以帮助应对和管理日益复杂的世界。近八十年来,以复杂性为依据的方法一直有望改变人们对复杂系统的理解和管理方式,最终帮助人们做出更好的决策。尽管复杂性科学潜力巨大,但在实践中,其应用往往局限于少数专业领域,并未成为主流政策辩论的一部分。为了了解为什么会出现这种情况,我们提出了一个问题:为什么复杂性科学仍处于萌芽状态,没有融入决策的核心?具体来说,我们要问的是,有哪些非技术性挑战和障碍阻碍了将复杂性科学纳入决策。为了解决这个问题,我们进行了广泛的文献综述。我们收集了零散的、讨论与在决策中使用复杂性科学有关的非技术性挑战的文本片段,并通过综合我们的发现将这些片段拼接成一个结构化的框架。我们的框架包括三个非技术性挑战的专题分组:(a) 管理、成本和采用挑战;(b) 有限的信任、沟通和接受度;(c) 道德障碍。针对确定的每项广泛挑战,我们都提出了一项缓解战略,以促进在决策中采用复杂性科学。最后,我们呼吁采取行动,进一步将复杂性科学纳入决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

The soft underbelly of complexity science adoption in policymaking: towards addressing frequently overlooked non-technical challenges

The soft underbelly of complexity science adoption in policymaking: towards addressing frequently overlooked non-technical challenges

The deepening integration of social-technical systems creates immensely complex environments, creating increasingly uncertain and unpredictable circumstances. Given this context, policymakers have been encouraged to draw on complexity science-informed approaches in policymaking to help grapple with and manage the mounting complexity of the world. For nearly eighty years, complexity-informed approaches have been promising to change how our complex systems are understood and managed, ultimately assisting in better policymaking. Despite the potential of complexity science, in practice, its use often remains limited to a few specialised domains and has not become part and parcel of the mainstream policy debate. To understand why this might be the case, we question why complexity science remains nascent and not integrated into the core of policymaking. Specifically, we ask what the non-technical challenges and barriers are preventing the adoption of complexity science into policymaking. To address this question, we conducted an extensive literature review. We collected the scattered fragments of text that discussed the non-technical challenges related to the use of complexity science in policymaking and stitched these fragments into a structured framework by synthesising our findings. Our framework consists of three thematic groupings of the non-technical challenges: (a) management, cost, and adoption challenges; (b) limited trust, communication, and acceptance; and (c) ethical barriers. For each broad challenge identified, we propose a mitigation strategy to facilitate the adoption of complexity science into policymaking. We conclude with a call for action to integrate complexity science into policymaking further.

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来源期刊
Policy Sciences
Policy Sciences Multiple-
CiteScore
9.70
自引率
9.40%
发文量
32
期刊介绍: The policy sciences are distinctive within the policy movement in that they embrace the scholarly traditions innovated and elaborated by Harold D. Lasswell and Myres S. McDougal. Within these pages we provide space for approaches that are problem-oriented, contextual, and multi-method in orientation. There are many other journals in which authors can take top-down, deductive, and large-sample approach or adopt a primarily theoretical focus. Policy Sciences encourages systematic and empirical investigations in which problems are clearly identified from a practical and theoretical perspective, are well situated in the extant literature, and are investigated utilizing methodologies compatible with contextual, as opposed to reductionist, understandings. We tend not to publish pieces that are solely theoretical, but favor works in which the applied policy lessons are clearly articulated. Policy Sciences favors, but does not publish exclusively, works that either explicitly or implicitly utilize the policy sciences framework. The policy sciences can be applied to articles with greater or lesser intensity to accommodate the focus of an author’s work. At the minimum, this means taking a problem oriented, multi-method or contextual approach. At the fullest expression, it may mean leveraging central theory or explicitly applying aspects of the framework, which is comprised of three principal dimensions: (1) social process, which is mapped in terms of participants, perspectives, situations, base values, strategies, outcomes and effects, with values (power, wealth, enlightenment, skill, rectitude, respect, well-being, and affection) being the key elements in understanding participants’ behaviors and interactions; (2) decision process, which is mapped in terms of seven functions—intelligence, promotion, prescription, invocation, application, termination, and appraisal; and (3) problem orientation, which comprises the intellectual tasks of clarifying goals, describing trends, analyzing conditions, projecting developments, and inventing, evaluating, and selecting alternatives. There is a more extensive core literature that also applies and can be visited at the policy sciences website: http://www.policysciences.org/classicworks.cfm. In addition to articles that explicitly utilize the policy sciences framework, Policy Sciences has a long tradition of publishing papers that draw on various aspects of that framework and its central theory as well as high quality conceptual pieces that address key challenges, opportunities, or approaches in ways congruent with the perspective that this journal strives to maintain and extend.Officially cited as: Policy Sci
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