提升供应链韧性和安全水平推动经济高质量发展的路径

在百年未有之大变局和中国进入高质量发展阶段的背景下,明确中国供应链安全面临的挑战与优势,提升中国供应链韧性和安全水平,是构建新发展格局、实现制造业高质量发展、维护国家经济安全的必然要求。中国供应链安全面临着关键核心技术“卡脖子”、供应链“断链”与产业跨境转移等风险,同时也具备产业体系优势、市场规模优势、举国体制优势和数字基建优势。为增强供应链韧性和安全水平,要以新型举国体制推动关键核心技术突破,推动数字化转型和数智供应链建设,优化制造业产业链高中低端产业布局,发挥超大规模内需市场的稳定作用,推进高水平对外开放,进而推动中国经济高质量发展。     

数字经济对我国市域农业经济韧性的影响效应与机理分析——基于系统GMM模型与动态门槛模型的检验

基于2011—2019年我国277个市域农业的面板数据,运用反事实方法科学测度了其经济韧性水平,并借助系统GMM模型、中介模型和动态门槛模型等方法,实证检验了数字经济对市域农业经济韧性的影响效应及作用机理。研究发现：数字经济显著增强了市域农业经济韧性,这一结论经一系列稳健性检验后仍能成立;机制分析结果表明,农业资本深化是数字经济提升市域农业经济韧性的重要路径。异质性分析表明,在东部、中部、西部地区和人力资本水平较高的地区,数字经济对市域农业经济韧性的影响效应更为显著,而对东北部地区的提升效应则不显著。动态门槛检验进一步揭示,数字经济对市域农业经济韧性的影响呈现边际递增的非线性特征,当数字经济发展水平越过特定门槛值（0147）时,数字经济对市域农业经济韧性的促进作用显著增强。     

The Need to Reconcile Concepts that Characterize Systems Facing Threats

Desirable system performance in the face of threats has been characterized by various management concepts. Through semistructured interviews with editors of journals in the fields of emergency response and systems management, a literature review, and professional judgment, we identified nine related and often interchangeably used system performance concepts: adaptability, agility, reliability, resilience, resistance, robustness, safety, security, and sustainability. A better understanding of these concepts will allow system planners to pursue management strategies best suited to their unique system dynamics and specific objectives of good performance. We analyze expert responses and review the linguistic definitions and mathematical framing of these concepts to understand their applications. We find a lack of consensus on their usage between interview subjects, but by using the mathematical framing to enrich the linguistic definitions, we formulate comparative visualizations and propose distinct definitions for the nine concepts. We present a conceptual framing to relate the concepts for management purposes.     

Ecosocial change and community resilience: The case of “Bönan” in glocal transition

ABSTRACT

The aim of this article was to identify and discuss ecosocial changes and community resilience mechanisms in a coastal fishing community of Sweden – Bönan. Data were collected through eight semi-structured interviews and field observations. An abductive thematic analysis was used to analyze data and background literature. The findings showed that Bönan has been exposed to a combination of ecosocial changes that have transformed the community, and therefore required community resilience interventions. This article concludes that social workers need to take an active part in ecosocial work for enhancing community resilience.     

Spatial Risk Analysis of Power Systems Resilience During Extreme Events

The increased frequency of extreme events in recent years highlights the emerging need for the development of methods that could contribute to the mitigation of the impact of such events on critical infrastructures, as well as boost their resilience against them. This article proposes an online spatial risk analysis capable of providing an indication of the evolving risk of power systems regions subject to extreme events. A Severity Risk Index (SRI) with the support of real‐time monitoring assesses the impact of the extreme events on the power system resilience, with application to the effect of windstorms on transmission networks. The index considers the spatial and temporal evolution of the extreme event, system operating conditions, and the degraded system performance during the event. SRI is based on probabilistic risk by condensing the probability and impact of possible failure scenarios while the event is spatially moving across a power system. Due to the large number of possible failures during an extreme event, a scenario generation and reduction algorithm is applied in order to reduce the computation time. SRI provides the operator with a probabilistic assessment that could lead to effective resilience‐based decisions for risk mitigation. The IEEE 24‐bus Reliability Test System has been used to demonstrate the effectiveness of the proposed online risk analysis, which was embedded in a sequential Monte Carlo simulation for capturing the spatiotemporal effects of extreme events and evaluating the effectiveness of the proposed method.     

Toward General Principles for Resilience Engineering

Maintaining the performance of infrastructure-dependent systems in the face of surprises and unknowable risks is a grand challenge. Addressing this issue requires a better understanding of enabling conditions or principles that promote system resilience in a universal way. In this study, a set of such principles is interpreted as a group of interrelated conditions or organizational qualities that, taken together, engender system resilience. The field of resilience engineering identifies basic system or organizational qualities (e.g., abilities for learning) that are associated with enhanced general resilience and has packaged them into a set of principles that should be fostered. However, supporting conditions that give rise to such first-order system qualities remain elusive in the field. An integrative understanding of how such conditions co-occur and fit together to bring about resilience, therefore, has been less clear. This article contributes to addressing this gap by identifying a potentially more comprehensive set of principles for building general resilience in infrastructure-dependent systems. In approaching this aim, we organize scattered notions from across the literature. To reflect the partly self-organizing nature of infrastructure-dependent systems, we compare and synthesize two lines of research on resilience: resilience engineering and social-ecological system resilience. Although some of the principles discussed within the two fields overlap, there are some nuanced differences. By comparing and synthesizing the knowledge developed in them, we recommend an updated set of resilience-enhancing principles for infrastructure-dependent systems. In addition to proposing an expanded list of principles, we illustrate how these principles can co-occur and their interdependencies.     

Tiered Approach to Resilience Assessment

Regulatory agencies have long adopted a three‐tier framework for risk assessment. We build on this structure to propose a tiered approach for resilience assessment that can be integrated into the existing regulatory processes. Comprehensive approaches to assessing resilience at appropriate and operational scales, reconciling analytical complexity as needed with stakeholder needs and resources available, and ultimately creating actionable recommendations to enhance resilience are still lacking. Our proposed framework consists of tiers by which analysts can select resilience assessment and decision support tools to inform associated management actions relative to the scope and urgency of the risk and the capacity of resource managers to improve system resilience. The resilience management framework proposed is not intended to supplant either risk management or the many existing efforts of resilience quantification method development, but instead provide a guide to selecting tools that are appropriate for the given analytic need. The goal of this tiered approach is to intentionally parallel the tiered approach used in regulatory contexts so that resilience assessment might be more easily and quickly integrated into existing structures and with existing policies.     

Farmers’ Risk‐Based Decision Making Under Pervasive Uncertainty: Cognitive Thresholds and Hazy Hedging

Researchers in judgment and decision making have long debunked the idea that we are economically rational optimizers. However, problematic assumptions of rationality remain common in studies of agricultural economics and climate change adaptation, especially those that involve quantitative models. Recent movement toward more complex agent‐based modeling provides an opportunity to reconsider the empirical basis for farmer decision making. Here, we reconceptualize farmer decision making from the ground up, using an in situ mental models approach to analyze weather and climate risk management. We assess how large‐scale commercial grain farmers in South Africa (n = 90) coordinate decisions about weather, climate variability, and climate change with those around other environmental, agronomic, economic, political, and personal risks that they manage every day. Contrary to common simplifying assumptions, we show that these farmers tend to satisfice rather than optimize as they face intractable and multifaceted uncertainty; they make imperfect use of limited information; they are differently averse to different risks; they make decisions on multiple time horizons; they are cautious in responding to changing conditions; and their diverse risk perceptions contribute to important differences in individual behaviors. We find that they use two important nonoptimizing strategies, which we call cognitive thresholds and hazy hedging, to make practical decisions under pervasive uncertainty. These strategies, evident in farmers' simultaneous use of conservation agriculture and livestock to manage weather risks, are the messy in situ performance of naturalistic decision‐making techniques. These results may inform continued research on such behavioral tendencies in narrower lab‐ and modeling‐based studies.     

Neoliberalisation,the social investment state and social work

ABSTRACT

This article focuses on the challenges to social work evolving from two major discourses contributing to the common sense contextualising social work within the new spirit of capitalism and the governing of the soul. Beside neo-liberal ideas and values challenging social work values and the welfare state, the question is also about managerialism. To what extent is the social worker able to contribute to liberating, reflexive critique, or exert pastoral power? I have chosen to see how the idea of the social investment state may be linked to Rose’s and Foucault’s ideas about expanding governmentality and end my discussion by relating to some of the early writing on social work’s challenges in confronting ideas and practices interpreted as neoliberalisation moves.