Interdependent Networks Research Articles

Utility coupling promotes cooperation in multiplayer snowdrift games on interdependent simplicial networks

Utility coupling promotes cooperation in multiplayer snowdrift games on interdependent simplicial networks

Cascading failures in interdependent networks with reinforced crucial nodes and dependency groups

Previous studies of group percolation models in interdependent networks with reinforced nodes have rarely addressed the effects of the degree of reinforced nodes and the heterogeneity of group size distribution. In this paper, a cascading failure model in interdependent networks with reinforced crucial nodes and dependency groups is investigated numerically and analytically. For each group, we assume that if all the nodes in a group fail on one network, a node on another network that depends on that group will fail. We find that rich percolation transitions can be classified into three types: discontinuous, continuous, and hybrid phase transitions, which depend on the density of reinforced crucial nodes, the group size, and the heterogeneity of group size distribution. Importantly, our proposed crucial reinforced method has higher reinforcement efficiency than the random reinforced method. More significantly, we develop a general theoretical framework to calculate the percolation transition points and the shift point of percolation types. Simulation results show that the robustness of interdependent networks can be improved by increasing the density of reinforced crucial nodes, the group size, and the heterogeneity of group size distribution. Our theoretical results can well agree with numerical simulations. These findings might develop a new perspective for designing more resilient interdependent infrastructure networks.

Robustness of edge-coupled interdependent networks with reinforced edges

Abstract Previous studies on cascade failures in interdependent networks have mainly focused on node coupling relationships. However, in realistic scenarios, interactions often occur at the edges connecting nodes rather than at the nodes themselves, giving rise to edge-coupled interdependent networks. In this article, we extend the model of partially edge-coupled interdependent networks by introducing reinforced edges with a ratio of ρ. We analyse the formation of finite surviving components in edge-coupled networks, wherein the reinforced edges can function and support their neighbouring nodes to form functional components. To accomplish this, we develop a framework through a detailed mathematical derivation of the proposed model. We then investigate the critical value ρ* of the reinforced edge ratio that can change the phase transition type of the network. Our model is verified by theoretical analysis, simulation experiments and real network systems. The results show that the introduction of a small proportion of reinforced edges in the edge-coupled interdependent network can avoid the sudden collapse of the network and significantly improve the robustness of the network.

The Role of Green Recruitment on Organizational Sustainability Performance: A Study within the Context of Green Human Resource Management

In light of the increasing recognition among modern business communities regarding the importance of implementing environmentally sustainable practices, this study thoroughly examines the concept of green recruitment (GR) and its subsequent impact on organizational sustainability performance (OSP). Situated within the shift from conventional to contemporary organizational frameworks that prioritize capacity, this study emphasizes the crucial importance of integrating sustainability into recruitment processes. This alignment ensures that human resource practices are in line with both environmental and organizational goals. The primary purpose emerges as a thorough examination and identification of sixteen critical factors that intersect GR and OSP, using insights from both the current literature and expert viewpoints, so this fills a crucial gap in the existing research. This study utilizes an integrated ISM-DEMATEL strategy to systematically reveal the hierarchical and relational patterns that are inherent in the connections between GR and OSP variables. This technique allows for a thorough comprehension of how these variables interact with each other. The findings highlight several important variables, emphasizing the complex network of interdependencies among the elements studied. The suggested model in this research encapsulates its originality, as it not only sheds light on the interdependent interactions for policy- and decision-makers but also establishes a foundation for future research in this field.

Robustness analysis of edge-coupled interdependent networks under different attack strategies

The robustness of interdependent networks has been a focus of research on complex networks, and the issue of attacks has become a popular research topic. However, some existing works have revealed significant vulnerabilities in interdependent networks, and the research on its robustness has been limited to node-coupled networks. While in reality, many networks are edge-coupled, and their robustness analysis has been overlooked. This paper constructs edge-coupled networks with positive, negative and random coupling based on the characteristics of edge-coupled interdependent networks. The sublayers use Erdös–Rényi (ER) random networks and scale-free (SF) networks, and four attack strategies, which includes intentional node/edge attack and random node/edge attack, are used to analyze the robustness of different edge-coupled interdependent networks. Seven edge/node importance indicators are proposed by considering node betweenness centrality, degree and eigenvector centrality, and these indicators are applied to attack strategies for result analysis, corresponding methods for enhancing robustness are proposed. The analysis results indicate that under intentional attacks, networks with negative coupling exhibit the strongest robustness, and its robustness can be influenced by their sublayers. In an environment with 500 nodes and an average degree of 4, when there is an ER network in the sublayer, protecting nodes/edges with high degree can improve the robustness of networks. If the sublayers are only composed of many SF networks, the betweenness centrality will have a greater impact when attacking most edges. While under random attacks, the networks with positive coupling exhibit the strongest robustness.

Modulatory role of RNA helicases in MBNL-dependent alternative splicing regulation

Muscleblind-like splicing regulators (MBNLs) activate or repress the inclusion of alternative splicing (AS) events, enabling the developmental transition of fetal mRNA splicing isoforms to their adult forms. Herein, we sought to elaborate the mechanism by which MBNLs mediate AS related to biological processes. We evaluated the functional role of DEAD-box (DDX) RNA helicases, DDX5 and DDX17 in MBNL-dependent AS regulation. Whole-transcriptome analysis and validation approaches revealed a handful of MBNLs-dependent AS events to be affected by DDX5 and DDX17 in mostly an opposite manner. The opposite expression patterns of these two groups of factors during muscle development and coordination of fetal-to-adult splicing transition indicate the importance of these proteins at early stages of development. The identified pathways of how the helicases modulate MBNL splicing activity include DDX5 and DDX17-dependent changes in the ratio of MBNL splicing isoforms and most likely changes in accessibility of MBNL-binding sites. Another pathway involves the mode of action of the helicases independent of MBNL activity. These findings lead to a deeper understanding of the network of interdependencies between RNA-binding proteins and constitute a valuable element in the discussion on developmental homeostasis and pathological states in which the studied protein factors play a significant role.

Assessing Leadership Capacity in the Food System: The Issue Leadership Scale.

The food system represents a complex, interrelated, and interdependent network of individuals and organizations. Despite the unique characteristics of the food system domain, there has never been a comprehensive analysis of leadership capacity amongst food system professionals. The present study provides an empirical assessment of food system leadership capacity using many leadership instruments. The study included pilot (n = 125) and primary (n = 4185) data collection across 27 food system-related leadership development programs. The results validate the Issue Leadership scale, which comprises seven capacity areas: action, change, communication, critical thinking, strategic planning and visioning, interpersonal traits and characteristics, leadership process, and leadership skills. The Issue Leadership scale captures both perception of importance and current skill level. The study results indicate that food system professionals perceived communication and critical thinking, strategic planning and visioning as the most important leadership capacity areas. Furthermore, respondents indicated the highest level of self-perceived skill in critical thinking, strategic planning and visioning, and interpersonal traits and characteristics. Overall, respondents had higher perceived importance levels (m = 4.17) than skill (m = 3.44), indicating the need for additional leadership capacity development amongst food system professionals. Respondents also indicated similar levels of opinion leadership (m = 3.92), servant leadership (m = 3.82), transformational leadership (m = 3.78), and transactional leadership (m = 3.70), providing an additional empirical assessment of food system professional leadership capacity.

Dynamics of cascades in spatial interdependent networks.

The dynamics of cascading failures in spatial interdependent networks significantly depends on the interaction range of dependency couplings between layers. In particular, for an increasing range of dependency couplings, different types of phase transition accompanied by various cascade kinetics can be observed, including mixed-order transition characterized by critical branching phenomena, first-order transition with nucleation cascades, and continuous second-order transition with weak cascades. We also describe the dynamics of cascades at the mutual mixed-order resistive transition in interdependent superconductors and show its similarity to that of percolation of interdependent abstract networks. Finally, we lay out our perspectives for the experimental observation of these phenomena, their phase diagrams, and the underlying kinetics, in the context of physical interdependent networks. Our studies of interdependent networks shed light on the possible mechanisms of three known types of phase transitions, second order, first order, and mixed order as well as predicting a novel fourth type where a microscopic intervention will yield a macroscopic phase transition.

Risk Interdependency Network Model for the Cost and Time of Pile Installation in Saudi Arabia, Using Partial Least Squares Structural Equation Modeling

Pile construction projects cause significant time and expense overruns. The pile installation activity is the primary reason for project underperformance and uncertainties. Additionally, the risks associated with pile installation are mostly considered independent in the overall risk management process, leading to inadequate risk assessment and response. However, few studies have evaluated the risks associated with pile installation. Thus, this study aims to establish the risks of the time and cost of pile installation, using an interdependency network model with a particular emphasis on sand and rocky terrain conditions. In addition, this study introduces a new method for establishing a model that considers the interrelationships among risks via a partial least squares structural equation model (PLS-SEM). The research methodology involves assessing the probability and impact of 53 risk factors of pile installation time and cost. Twelve pile construction experts participated in this assessment. Then, a Monte Carlo Simulation was utilized before the data were integrated into the PLS-SEM. The research findings reveal that the site and economic risks indirectly affect the cost of installing pile in sand through construction risks. Also, the risk group comprising site and equipment risks indirectly affects the cost of installing pile in rock through design risks. This study’s findings will help construction organizations to improve time and cost risk assessments for pile installation projects.

Dependence matters: Statistical models to identify the drivers of tie formation in economic networks

Networks are ubiquitous in economic research on organizations, trade, and many other areas. However, while economic theory extensively considers networks, no general framework for their empirical modeling has yet emerged. We thus introduce two different statistical models for this purpose – the Exponential Random Graph Model (ERGM) and the Additive and Multiplicative Effects network model (AME). Both model classes can account for network interdependencies between observations, but differ in how they do so. The ERGM allows one to explicitly specify and test the influence of particular network structures, making it a natural choice if one is substantively interested in estimating endogenous network effects. In contrast, AME captures these effects by introducing actor-specific latent variables affecting their propensity to form ties. This makes the latter a good choice if the researcher is interested in capturing the effect of exogenous covariates on tie formation without having a specific theory on the endogenous dependence structures at play. After introducing the two model classes, we showcase them through real-world applications to networks stemming from international arms trade and foreign exchange activity. We further provide full replication materials to facilitate the adoption of these methods in empirical economic research.

Measuring the impact of a failing participant in payment systems

Large banks and critical financial market infrastructures (FMIs) that are not able to fulfill their payment obligations, for example following a bankruptcy or cyber-attack, can be a source of financial instability and contagion in the financial system. This paper develops a composite risk indicator to evaluate the criticality of participants in a large value payment system network, combining liquidity risk (i.e. size of incoming and outgoing payments) and systemic impact or interconnections between network participants in one approach. It is applied, as a proof of concept, to the TARGET2 payment system that links banks and FMIs in a tight network of interdependencies. We find that the most critical participants in TARGET2 are other payment systems (large value and retail) because of the underlying gross size of their payment flows. Some banks may be critical, but this is mainly due to their interconnectedness with other TARGET2 participants. Central counterparties and central securities depositories are less critical to the payment system. Our findings can be used by (1) financial stability experts to evaluate the impact of a failing critical participant in the financial system, and (2) central banks in their role as payment system operator and overseer. Besides, it feeds into policy discussions on payment system access, oversight, and crisis management.

Towards a new era in the governance of integrated activation: A systematic review of the literature on the governance of welfare benefits and employment‐related services in Europe (2010–21)

AbstractThis article presents the results of a systematic literature review of research articles (N = 72) to study the governance logic of integrated activation policies and the problems relating to reintegrating welfare benefits with services. The inductive study of the problems indicated in the literature demonstrates both the vertical and horizontal aspects of the governance of integrated activation at the street level: challenges are tied to the top‐down activation policy; requirements and strategies of delivering benefits and services; collaboration and coordination in delivery chains; and risks and inequality that streel‐level bureaucrats are trying to deal with in their work. The results point primarily to flaws in the vertical governance of activation, such as frontline work problems and collaborative practices between different actors and agencies. Moreover, some problems relating to collaboration and coordination, pointed towards the challenges in horizontal governance of activation. The article, however, demonstrates how the governance of integrated activation requires a coupling of these different streams of governance and understanding governance as a complex network of interdependencies and causal connections between institutions, organisations, and co‐production with end users.

Attack–Defense Game in Interdependent Networks: A Functional Perspective

Attack–Defense Game in Interdependent Networks: A Functional Perspective

Improving resilience of high-speed train by optimizing repair strategies

High-speed trains (HSTs) are used to transport passengers to destinations efficiently and safely. However, when HST units fail, strategies for repairing them are not available. Hence, to optimize repair strategies, an interdependent network is used to model an HST, and a metric of resilience based on network theory is introduced. Based on practical factors, an interdependent machine–electricity–communication network (IMECN) and related cascading failure models are developed. Comprehensive robustness metrics for the IMECN and nodes are proposed considering the topology of networks and functional features of nodes. Accordingly, a resilience optimization model of the IMECN subject to disturbances is formulated and solved using a tabu search (TS) algorithm. Finally, a real-world HST is considered to analyze the optimal repair strategy for different numbers of failed nodes. Analysis results show that the recovery process under the optimal repair strategy has at most three stages. When a few nodes and less than half of the nodes fail, the highest and lowest levels of the IMECN are achieved, respectively. Moreover, the characteristics of the preferentially repaired node in terms of importance, vulnerability, network type, and interdependency are analyzed. Results indicate that the optimal repair strategy is not necessarily determined by topological metrics.

Auctions for resource allocation and decentralized restoration of interdependent networks

Auctions for resource allocation and decentralized restoration of interdependent networks

Optimal defense strategy selection method for CPS considering integrated cyber–physical losses

Cyber-attacks against the cyber–physical power system (CPPS) may lead to major power outages and even system collapse in severe cases. In order to quantify the attack losses and select optimal strategies to defend against cyber-attacks, this paper proposes a computational model of integrated cyber–physical losses based on the theory of interdependent network. Based on the multiple coupling relationship between cyber system and physical network, the monitoring system is regarded as the cyber–physical interaction layer, and the information network operation constraint, physical system load reduction constraint, and monitoring equipment operation constraint are established respectively to analyze the impact on another network after a failed node appears in one layer of network, and proposed the cyber–physical integrated loss objective function. The offensive and defensive processes are abstracted into a two-player zero-sum game model, which evolves into a multi-stage game according to the changes in the system state during the game, and the integrated cyber–physical loss is used as the game gain of both the attacker and defender, and the Minimax-Q algorithm is introduced to solve for the optimal gain and select the optimal defense strategy. Finally, the IEEE 30 node cyber–physical system is used as a simulation example to verify whether the proposed loss calculation model can effectively quantify the losses caused by the attack on the information network and the power grid, and has practical guidance for the selection of the optimal defense strategy.

Beyond the institution versus home care dichotomy: Lessons from a feeding‐tube medical home

AbstractDecades of rights‐based advocacy for people with disabilities have transitioned long‐term care in the United States from institutional settings to home‐based care provided by interdependent care networks. This paper argues that policies and practices within these home‐based care systems unintentionally produce and often perpetuate unrecognized structural violence on the recipients of care and the caregivers. Understanding the caregivers' experiences through a case study of a Facebook feeding tube family support group exposes the geographic realities and ableist underpinnings of the home‐based care model that undergird this violence. Further, I illustrate the contradictions of “home is best” ideology by focusing on three interwoven themes: structural dependency on unpaid mother‐experts, spatio‐temporal erasure through decentralization, and invasive surveillance structures. This research attends to how home‐based care, as a practice and a place, reflects broader patriarchal, gendered, and neoliberal concepts of autonomy and individual rights as expressed through policies like “person‐centered” care and the medical home model. While this analysis has theoretical, methodological, and policy implications, more important is the contextualization of family experiences that sometimes impacts life and death.

Percolation behavior analysis of weighted edge-coupled interdependent networks

The robustness of interdependent networks has received extensive attention from the inter-disciplinary fields. In reality, many interdependent systems have interdependence relationships not only between nodes but also between edges. Different from previous studies focusing on edge-coupled interdependent networks without consideration on coupling strength, in this paper, a weighted edge-coupled interdependent network model with coupling strength is proposed. Then, the cascading failure propagation mechanism caused by attacking a small percentage of edges is studied. Based on the self-consistent probability theory, theoretical framework is established to provide the mathematical analysis of robustness of weighted edge-coupled interdependent networks under edge attacks. The current results can help to understand the vulnerability of interdependent networks and provide useful suggestions for the protection and optimization of complex networked systems.

Multivariate recovery coupling in interdependent networks with cascading failure.

Interdependent networks are susceptible to catastrophic consequences due to the interdependence between the interacting subnetworks, making an effective recovery measure particularly crucial. Empirical evidence indicates that repairing the failed network component requires resources typically supplied by all subnetworks, which imposes the multivariate dependence on the recovery measures. In this paper, we develop a multivariate recovery coupling model for interdependent networks based on percolation theory. Considering the coupling structure and the failure-recovery relationship, we propose three recovery strategies for different scenarios based on the local stability of nodes. We find that the supporting network plays a more important role in improving network resilience than the network where the repaired component is located. This is because the recovery strategy based on the local stability of the supporting nodes is more likely to obtain direct benefits. In addition, the results show that the average degree and the degree exponent of the networks have little effect on the superior performance of the proposed recovery strategies. We also find a percolation phase transition from first to second order, which is strongly related to the dependence coefficient. This indicates that the more the recovery capacity of a system depends on the system itself, the more likely it is to undergo an abrupt transition under the multivariate recovery coupling. This paper provides a general theoretical frame to address the multivariate recovery coupling, which will enable us to design more resilient networks against cascading failures.

Percolation phase transition in the heterogeneous multi-coupled interdependent network

In previous studies, complex system models have often been set up in an oversimplified manner and the failure mechanism for nodes affected by each other is not correspond to reality. Accordingly, we develop a new model of heterogeneous multi-coupled interdependent networks and analyze the change in the giant component of the network after the attack in conjunction with the load redistribution mechanism. We first analyze the cascading failure process of the network analytically by recursive methods, estimate the critical phase transition threshold and the size of the giant component of the remaining network after network percolation, and find that the threshold of the WS sub-network is positively related to the average degree, and the BA sub-network is related to the power exponent λ of the distribution. When λ is less than or equal to 2, there is always a giant component in the network. After λ is greater than 3.4788⋯, there is no giant component. When λ is between 2 to 3.4788⋯, we found that the threshold of the sub-network is more influenced by the proportion of attacks (p1 and p2), and when p1 is larger, the sub-networks interact with each other, resulting in a smaller threshold for the BA sub-network, while the threshold of the WS sub-network is smaller in other cases. Finally, the cross-sectional comparison illustrates that as λ increases to 3.4788⋯, the robustness of the BA sub-network increases, contrary to the findings for single-layer networks. Overall, the heterogeneous multi-coupled interdependent network is more robust, and the giant component is greatly affected by the low robust sub-network, but its existence is related to the stock of nodes.